Walter Sisulu University
PROSPECTUS 2014
Faculty of Science, Engineering
and Technology
School of Mathematical & Computational Sciences
www.wsu.ac.za
FACULTY OF SCIENCE, ENGINEERING AND
TECHNOLOGY
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
PROSPECTUS 2014
1
2014
PROSPECTUS
TABLE OF CONTENTS
1
SCHOOL ADMINISTRATIVE STAFF .................................................................................. 5
1.1 Departments Academic and Administrative Staff............................................................... 5
1.1.1 Department of Applied Mathematics................................................................................ 5
1.1.1.1
Academic Staff.............................................................................................................. 5
1.1.1.2 Administrative & Academic Support Staff......................................................................... 5
1.1.2
Department of Mathematics............................................................................................ 5
1.1.2.1
Academic Staff.............................................................................................................. 5
1.1.2.2
Administrative & Academic Support Staff......................................................................... 6
1.1.3 Department of Statistics................................................................................................. 6
1.1.3.1 Academic Staff.............................................................................................................. 6
1.1.3.2
Administrative & Academic Support Staff......................................................................... 7
1.2
Introduction & Welcome by the Director of School............................................................ 7
1.2.1
School Campuses, Sites and the New School Concept....................................................... 7
1.2.2
Merger of Legacy Institutions......................................................................................... 8
1.2.3
Two Tier Governance Structure....................................................................................... 8
1.2.4
Academic Focus of the School......................................................................................... 8
1.3 School Vision & Mission.................................................................................................. 9
1.3.1
Vision of the School....................................................................................................... 9
1.3.2
Mission of the School..................................................................................................... 9
1.4
School Rules.................................................................................................................. 9
1.5 Minimum Admission Requirements (for the regular programmes).................................... 10
1.5.1 Selection Criteria for New Students............................................................................... 10
1.6 Minimum Admission Requirements and Programme Characteristics
(for the extended programmes).................................................................................... 11
1.7
Programme Rules (Undergraduate)............................................................................... 12
1.7.1
Admission Rules........................................................................................................... 12
1.7.2 Progression Rules........................................................................................................ 12
1.7.2.1
Re-Admission of Continuing Students............................................................................ 12
1.7.3
Exit Rules.................................................................................................................... 13
1.7.3.1
Completion Rules......................................................................................................... 13
1.7.3.2
Exclusion Rules............................................................................................................ 13
1.8
Programme Rules (Honours)......................................................................................... 13
1.8.1
Admission Rules........................................................................................................... 13
1.8.2 Progression Rules........................................................................................................ 13
1.8.2.1
Re-Admission of Continuing Students............................................................................ 13
1.8.3
Exit Rules.................................................................................................................... 13
1.8.3.1
Completion Rules......................................................................................................... 13
1.8.3.2
Exclusion Rules............................................................................................................ 14
1.9
Departments and Programmes...................................................................................... 14
1.9.1
Department of Applied Mathematics.............................................................................. 14
1.9.1.1
Information about Department..................................................................................... 14
1.9.1.2
Mission of the Department............................................................................................ 14
1.9.1.3
Goals of the Department.............................................................................................. 14
1.9.1.4
Student Societies in the Department............................................................................. 15
1.9.1.5
Programmes in the Department.................................................................................... 15
1.9.1.5.1
BSc Applied Mathematics.............................................................................................. 15
1.9.1.5.1.1
Entrepeneurship & Professional Development of Students............................................... 15
1.9.1.5.1.2
Career Opportunities.................................................................................................... 15
1.9.1.5.1.3
Purpose of Qualification................................................................................................ 15
1.9.1.5.1.4
Exit Level Outcomes of the Programme......................................................................... 15
1.9.1.5.1.5
Programme Characteristics........................................................................................... 15
1.9.1.5.1.5.1
Academic and Research Orientated Study...................................................................... 15
1.9.1.5.1.5.2
Practical Work............................................................................................................. 16
1.9.1.5.1.5.3
Teaching and Learning Methodology............................................................................. 16
1.9.1.5.1.6
Programme Information............................................................................................... 16
1.9.1.5.1.6.1Curriculum.................................................................................................................. 16
1.9.1.5.1.6.1.1 Core and Foundation Modules....................................................................................... 16
1.9.1.5.1.6.1.2Electives...................................................................................................................... 17
1.9.1.5.1.6.1.3 Pre-Requisite Courses.................................................................................................. 18
1.9.1.5.1.6.2
Award Of Qualification.................................................................................................. 19
1.9.1.5.1.6.3
Programme Tuition Fees............................................................................................... 19
1.9.1.5.1.6.4Articulation.................................................................................................................. 19
1.9.1.5.1.6.5
Core Syllabi of Subjects Offered.................................................................................... 19
1.9.1.5.2
BSc Applied Mathematics (Extended Programme)........................................................... 22
1.9.1.5.2.1 Curriculum.................................................................................................................. 23
1.9.1.5.2.1.1
Core and Foundation Modules....................................................................................... 23
1.9.1.5.2.1.2Electives...................................................................................................................... 24
1.9.1.5.2.1.3
Pre-Requisite Courses.................................................................................................. 24
1.9.1.5.2.2
Award of Qualification.................................................................................................. 24
SCHOOL OF MATHEMATICAL AND
2
COMPUTATIONAL SCIENCES
1.9.1.5.2.3
Programme Tuition fees................................................................................................ 25
1.9.1.5.2.4Articulation.................................................................................................................. 25
1.9.1.5.2.5
Core Syllabi Of Courses Offered.................................................................................... 25
1.9.2
Department of Mathematics.......................................................................................... 26
1.9.2.1
Information about Department..................................................................................... 26
1.9.2.2
Mission of the Department............................................................................................ 27
1.9.2.3
Goals of the Department.............................................................................................. 27
1.9.2.4
Student Societies in the Department............................................................................. 27
1.9.2.5
Programmes in the Department.................................................................................... 27
1.9.2.5.1
BSc Mathematics......................................................................................................... 27
1.9.2.5.1.1
Entrepeneurship & Professional Development of Students............................................... 27
1.9.2.5.1.2
Career Opportunities.................................................................................................... 28
1.9.2.5.1.3
Purpose of Qualification................................................................................................ 28
1.9.2.5.1.4
Exit Level Outcomes of the Programme......................................................................... 28
1.9.2.5.1.5
Programme Characteristics........................................................................................... 28
1.9.2.5.1.5.1
Academic and Research Orientated............................................................................... 28
1.9.2.5.1.5.2
Practical Work............................................................................................................. 28
1.9.2.5.1.5.3
Teaching and Learning Methodology............................................................................. 28
1.9.2.5.1.6 Programme Information............................................................................................... 29
1.9.2.5.1.6.1Curriculum.................................................................................................................. 29
1.9.2.5.1.6.1.1 Core and Foundation Modules....................................................................................... 29
1.9.2.5.1.6.1.2Electives...................................................................................................................... 30
1.9.2.5.1.6.1.3 Pre-Requisite Courses.................................................................................................. 31
1.9.2.5.1.6.2
Award of Qualification.................................................................................................. 31
1.9.2.5.1.6.3
Programme Tuition Fees............................................................................................... 32
1.9.2.5.1.6.4Articulation.................................................................................................................. 32
1.9.2.5.1.6.5
Core Syllabi of Subjects Offered.................................................................................... 32
1.9.2.5.2 BSc Mathematics (Extended Programme)...................................................................... 36
1.9.2.5.2.1 Curriculum.................................................................................................................. 36
1.9.2.5.2.1.1
Core and Foundation Modules....................................................................................... 36
1.9.2.5.2.1.2Electives...................................................................................................................... 36
1.9.2.5.2.1.3
Pre-Requisite Courses.................................................................................................. 37
1.9.2.5.2.2
Core Syllabi Of Courses Offered.................................................................................... 37
1.9.2.5.3 Honours BSc Mathematics............................................................................................ 39
1.9.2.5.3.1 Entrepreneurship & Professional Development of Students.............................................. 39
1.9.2.5.3.2
Career Opportunities.................................................................................................... 39
1.9.2.5.3.3
Purpose of Qualification................................................................................................ 39
1.9.2.5.3.4
Exit Level Outcomes of the Programme......................................................................... 39
1.9.2.5.3.5
Programme Characteristics........................................................................................... 39
1.9.2.5.3.5.1
Academic and Research Orientated............................................................................... 39
1.9.2.5.3.5.2
Practical Work............................................................................................................. 39
1.9.2.5.3.5.3
Teaching and Learning Methodology............................................................................. 39
1.9.2.5.3.6 Programme Information............................................................................................... 40
1.9.2.5.3.6.1
Minimum Admission Requirements................................................................................ 40
1.9.2.5.3.6.2
Selection Criteria for New Students............................................................................... 40
1.9.2.5.3.6.3Curriculum.................................................................................................................. 40
1.9.2.5.3.6.3.1 Required Modules........................................................................................................ 40
1.9.2.5.3.6.3.2 Courses Offered........................................................................................................... 41
1.9.2.5.3.6.3.3 Pre-Requisite Courses.................................................................................................. 41
1.9.2.5.3.6.4
Award of Qualification.................................................................................................. 41
1.9.2.5.3.6.5
Programme Tuition Fees............................................................................................... 41
1.9.2.5.3.6.6Articulation.................................................................................................................. 41
1.9.2.5.3.6.7
Core Syllabi of Subjects Offered.................................................................................... 42
1.9.2.5.4
MSc Mathematics......................................................................................................... 44
1.9.2.5.4.1
Entrepreneurship & Professional Development of Students.............................................. 44
1.9.2.5.4.2
Career Opportunities.................................................................................................... 45
1.9.2.5.4.3
Purpose of Qualification................................................................................................ 45
1.9.2.5.4.4
Exit Level Outcomes of the Programme......................................................................... 45
1.9.2.5.4.5
Programme Characteristics........................................................................................... 45
1.9.2.5.4.5.1
Academic and Research Orientated............................................................................... 45
1.9.2.5.4.5.2
Practical Work............................................................................................................. 45
1.9.2.5.4.5.3
Teaching and Learning Methodology............................................................................. 45
1.9.2.5.4.6
Programme Information............................................................................................... 45
1.9.2.5.4.6.1
Minimum Admission Requirements................................................................................ 45
1.9.2.5.4.6.2
Selection Criteria for New Students............................................................................... 45
1.9.2.5.4.6.1Curriculum.................................................................................................................. 46
1.9.2.5.4.6.2
Available Topics/Areas of Research................................................................................ 46
1.9.2.5.4.6.3
Award of Qualification.................................................................................................. 46
1.9.2.5.4.6.4
Programme Tuition Fees............................................................................................... 46
1.9.2.5.4.6.5Articulation.................................................................................................................. 46
1.9.2.5.4.6.6
Service Modules offered by the Department................................................................... 47
3
2014
PROSPECTUS
1.9.3
Department of Statistics............................................................................................... 47
1.9.3.1
Information about Department..................................................................................... 48
1.9.3.2
Mission of the Department............................................................................................ 48
1.9.3.3 Goals of the Department.............................................................................................. 48
1.9.3.4
Student Societies in the Department............................................................................. 48
1.9.3.5
Programmes in the Department.................................................................................... 48
1.9.3.5.1
BSc Applied Statistical Science...................................................................................... 48
1.9.3.5.1.1
Entrepeneurship & Professional Development of Students............................................... 48
1.9.3.5.1.2
Career Opportunities.................................................................................................... 48
1.9.3.5.1.3
Purpose of Qualification................................................................................................ 48
1.9.3.5.1.4
Exit Level Outcomes of the Programme......................................................................... 48
1.9.3.5.1.5
Programme Characteristics........................................................................................... 50
1.9.3.5.1.5.1
Academic and Research Orientated Study...................................................................... 50
1.9.3.5.1.5.2
Practical Work............................................................................................................. 50
1.9.3.5.1.5.3
Teaching and Learning Methodology............................................................................. 50
1.9.3.5.1.6 Programme Information............................................................................................... 50
1.9.3.5.1.6.1 Curriculum.................................................................................................................. 50
1.9.3.5.1.6.1.1 Core and Foundation Modules....................................................................................... 50
1.9.3.5.1.6.1.2Electives...................................................................................................................... 51
1.9.3.5.1.6.1.3 Pre-Requisite Courses.................................................................................................. 52
1.9.3.5.1.6.2
Award of Qualification.................................................................................................. 53
1.9.3.5.1.6.3
Programme Tuition Fees............................................................................................... 53
1.9.3.5.1.6.4Articulation.................................................................................................................. 53
1.9.3.5.1.6.5
Core Syllabi of Subjects Offered.................................................................................... 53
1.9.3.5.2
BSc Applied Statistical Science (Extended Programme)................................................... 56
1.9.3.5.2.1 Curriculum.................................................................................................................. 57
1.9.3.5.2.1.1
Core and Foundation Modules....................................................................................... 57
1.9.3.5.2.1.2Electives...................................................................................................................... 57
1.9.3.5.2.1.3
Pre-Requisite Courses.................................................................................................. 58
1.9.3.5.2.2
Award of Qualification.................................................................................................. 58
1.9.3.5.2.3
Programme Tuition Fees............................................................................................... 58
1.9.3.5.2.4Articulation.................................................................................................................. 58
1.9.3.5.2.5
Core Syllabi of Courses Offered..................................................................................... 59
1.9.2.5.3 BSc Honours (Statistical Science).................................................................................. 60
1.9.3.5.3.1 Entrepreneurship & Professional Development of Students.............................................. 60
1.9.3.5.3.2
Career Opportunities.................................................................................................... 61
1.9.3.5.3.3
Purpose of Qualification................................................................................................ 61
1.9.3.5.3.4
Exit Level Outcomes of the Programme......................................................................... 61
1.9.3.5.3.5
Programme Characteristics........................................................................................... 61
1.9.3.5.3.5.1
Academic and Research Orientated............................................................................... 61
1.9.3.5.3.5.2
Practical Work............................................................................................................. 61
1.9.3.5.3.5.3
Teaching and Learning Methodology............................................................................. 61
1.9.3.5.3.6 Programme Information............................................................................................... 61
1.9.3.5.3.6.1
Minimum Admission Requirements................................................................................ 61
1.9.3.5.3.6.2
Selection Criteria for new students................................................................................ 62
1.9.3.5.3.6.1Curriculum.................................................................................................................. 62
1.9.3.5.3.6.1.1 Core and Foundation Modules....................................................................................... 62
1.9.3.5.3.6.1.2Electives...................................................................................................................... 62
1.9.3.5.3.6.1.3 Pre-Requisite Courses & Available Electives.................................................................... 62
1.9.3.5.3.6.2
Award of Qualification.................................................................................................. 62
1.9.3.5.3.6.3
Programme Tuition Fees............................................................................................... 62
1.9.3.5.3.6.4Articulation.................................................................................................................. 63
1.9.3.5.3.6.5
Core Syllabi of Subjects Offered.................................................................................... 63
1.9.3.5.4
MSc (Statistical Science)............................................................................................... 66
1.9.3.5.4.1
Entrepeneurship & Professional Development of Students............................................... 66
1.9.3.5.4.2
Career Opportunities.................................................................................................... 67
1.9.3.5.4.3
Purpose of Qualification................................................................................................ 67
1.9.3.5.4.4
Exit Level Outcomes of the Programme......................................................................... 67
1.9.3.5.4.5
Programme Characteristics........................................................................................... 67
1.9.3.5.4.5.1
Academic and Research Orientated............................................................................... 67
1.9.3.5.4.5.2
Practical Work............................................................................................................. 67
1.9.3.5.4.5.3
Teaching and Learning Methodology............................................................................. 67
1.9.3.5.4.6
Programme Information............................................................................................... 67
1.9.3.5.4.6.1
Minimum Admission Requirements................................................................................ 67
1.9.3.5.4.6.2
Selection Criteria for New Students............................................................................... 68
1.9.3.5.4.6.1Curriculum.................................................................................................................. 68
1.9.3.5.4.6.2
Available Topics/Areas of Research................................................................................ 68
1.9.3.5.4.6.3
Award of Qualification.................................................................................................. 68
1.9.3.5.4.6.4
Programme Tuition Fees............................................................................................... 68
1.9.3.5.4.6.5Articulation.................................................................................................................. 68
1.9.3.5.4.6.6
Service Modules Offered by the Department.................................................................. 69
SCHOOL OF MATHEMATICAL AND
4
COMPUTATIONAL SCIENCES
1
SCHOOL ADMINISTRATIVE STAFF
Designation
Director of School
School Officer
Secretary
1.1
Name
Qualifications
Prof. SN Mishra
MSc, D.Phil (Allahabad)
Vacant
Mrs V Ndamase - Nee Maliwa ND: Office Management &Technology
(Ect)
Departments Academic and Administrative Staff
1.1.1 Department of Applied Mathematics
1.1.1.1 Academic Staff
Designation
Name
Qualifications
Professor
Associate Professor
Acting HOD/Senior
Lecturer
Junior Lecturer Parttime
Lecturer Part- time
Junior Lecturer
Part- time
Vacant
Dr W Sinkala
Dr M Chaisi
BSc (UNZA), MSc (UZ), PhD (UKZN)
BSc (NUL), MSc (Wales), PhD (UKZN)
Mr M Makurumure
BSc, BSc (Hons) (NUST)
Mr T F Nkalashe
Mr C Kakuli
BSc, BSc (Hons)(Unitra) , MSc(WSU)
BSc, BSc (Hons)
1.1.1.2 Administrative & academic support staff
None
1.1.2
Department of Mathematics
1.1.2.1 Academic Staff
Site: NMD
Designation
Name
Qualifications
Professor
Professor/Head of
Department
Acting HOD/
Lecturer
Senior Lecturer
Senior Lecturer
Prof. SN Mishra
Vacant
MSc, D.Phil (Allahabad)
Mrs RM Panicker
BSc, B.Ed, MSc(M.G. Univ. Kerala)
Lecturer
Lecturer
Junior Lecturer
Mr W Mbava
Mrs LS Abraham
Mr VB Lucwaba
Vacant
Vacant
BSc, BSc (Hons),MSc (UZ)
BSc,MSc, B.Ed (MG university)
BSc, BSc,Hons (Unitra)
5
2014
PROSPECTUS
Junior Lecturer/Part- Mrs N Thomas
time
BSc, BSc,Hons (Unitra)
Site: IBIKA
Designation
Name
Qualifications
Acting Site HOD /
Senior Lecturer
Senior Lecturer
Lecturer
Lecturer
Lecturer
Lecturer/Temporary
Mr MS Majova
BSc, HED, BSc (Hons)(Unitra), M. Ed
( Unitra)
BSc (Hons)(Unitra), M. Sc ( Unitra)
BSc, BSc (Hons)HDE(Unitra)
BSc,BSc (Hons)(Unitra)
BSc, BSc (Hons),MSc(Unitra) PhD (RU)
Lecturer/Temporary
Mr S Jama
Mr PS Jaca
Mrs P Stofile
Ms F Tonjeni
Dr S Stofile
Mr C Kakuli
Site: BC
Designation
Name
Qualifications
Acting Site HOD /
Lecturer
Mrs J Coetzee
BSc (Hons)(UNISA),
BSc(UP),HDE(UNISA), B.Ed(RAU), MSc
(Math. Ed) ( UNISA)
Senior Lecturer
Lecturer
Vacant
Ms M Mbebe
Lecturer/Temporary
Lecturer
Mr NE Mbhele
Mr M Mofoka
Lecturer
Lecturer/Temporary
Ms L Bester
Mrs E Oberholster
MBA (NMMU),
BSc(RHODES),BSc(HONS)(UWC)
BSc (UFH), BSc (Hons) (UFH)
(UFH), BSc (HONS)(UFH),NTD
MECHENG
BSc (UP), BSc (HONS)(UP)
MED (RHODES), BCOM (UNISA),
BED (UCT), UED, (RHODES), BSC
(RHODES)
BSc (HONS) (UFH), BSc (UFH)
Lecturer
Mr B Mtiya
1.1.2.2 Administrative & academic support staff
None
1.1.3 Department of Statistics
1.1.3.1 Academic Staff
Designation
Name
Professor/Head of
Department
Associate Professor
Vacant
Qualifications
Prof KW Binyavanga
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
BSc.Hons, MA (Dar es Salaam), PhD
(Stellenbosch)
6
Lecturer
Mr JS Nasila
Senior Lecturer
Junior Lecturer
Junior Lecturer /
Temporary
Junior Lecturer/
Part-time
Dr H Moolman
Mr L Majeke
Mr CE Pokoo-Sonny
BSc (Madras), Post Bacc. Diploma
(SFU), M Sc (Simon Fraser)
BSc, BSc (Hons) (Unitra), MSc (UFH)
BA (Ghana), P.G.D.E (Cape Coast),
BSc (Hons) (WSU), MSc (Rhodes)
BSc, BSc (Hons) (UFH)
Ms NN Matu
1.1.3.2 Administrative & academic support staff
None
1.2
Introduction & Welcome by the Director of School
The School of Mathematical and Computational Sciences at Walter Sisulu University like other
such schools in the country and elsewhere, is supposed to play a vital role in serving the current
needs of the country. This recognition has to a large extent informed the nature of programmes
that are offered in the school. Another factor that has influenced the characteristics of our
programmes is the emergence of computers and the “computerisation” of mathematics that has
taken place over a number of years. The tremendous impact that this has had on the teaching
and research in mathematics cannot be ignored. In this light, the School of Mathematical and
Computational Sciences offers programmes that strive to strike a good balance between theory
and computation.
Currently, the school offers undergraduate and postgraduate programmes in specialised areas
of Applied Mathematics, Mathematics and Statistics. These programmes, in particular, the
undergraduate programmes, are somewhat interdisciplinary in nature and provide a base from
which one can build a career in a mathematical-sciences-related area or proceed to do basic
research in Mathematical Sciences.
There is an important role that the school plays in many programmes offered in other schools
and faculties in that these programmes include courses/modules that are taught by departments
in the school. Currently, a large number of students from Engineering, Education and Economic
Sciences are serviced by the School of Mathematical and Computational Sciences.
1.2.1
School campuses, sites and the new School concept
The School of Mathematical and Computational Sciences extends over three campuses of
the Walter Sisulu University, Mthatha, Butterworth and Buffalo City, and comprises three
departments, namely, Applied Mathematics, Mathematics and Statistics. The school offers
degree programmes at the levels of BSc, BSc (Hons) and MSc in the respective departments.
The following is a summary of programmes that are offered by the School of Mathematical and
Computational Sciences.
7
2014
PROSPECTUS
Department
Duration
Full-time
Department
BSc Applied Mathematics – ECP*
4yrs
of Applied
BSc Applied Mathematics
3yrs
Mathematics
MSc
2yrs
Department of BSc Mathematics - ECP*
4yrs
Mathematics
BSc Mathematics
3yrs
Honours BSc Mathematics
1yr
MSc Mathematics
2yrs
Department of BSc Applied Statistical Science - ECP* 4yrs
Statistics
BSc Applied Statistical Science
4yrs
Honours BSc Applied Statistical Science 1yr
MSc Statistical Science
2yrs
ECP*: Extended Degree Programme.
1.2.2
Programmes offered
Duration
Part-time
N/A
N/A
4 yrs
N/A
N/A
2 yrs
4 yrs
N/A
2 yrs
2 yrs
4 yrs
Delivery
Sites
NMD
NMD
NMD
NMD
NMD
NMD
NMD
NMD
NMD
NMD
NMD
Merger of legacy institutions
Walter Sisulu University was formed on 1 July 2005 through the merger of Border Technikon,
Eastern Cape Technikon and the University of Transkei (Unitra). The business of two of the
departments in the School of Mathematical and Computational Sciences, namely, Applied
Mathematics and Statistics, is confined to the NMD site, in Mthatha, while that of the department
of mathematics extends beyond NMD to Ibika, (Butterworth) Potsdam, Chiselhurst and College
Street sites (East London).
1.2.3
Two Tier Governance Structure
All the major programmes offered in the school are located at the Nelson Mandela Drive (NMD)
Site. In Buffalo City (Potsdam, Chiselhurst and College Street) and Ibika (Butterworth) the
courses offered are essentially service courses to engineering programmes. HODs for the
respective departments are stationed at NMD, and are assisted by site HODs at other delivery
sites. HODs report to the director of the school, who as academic head oversees the academic
programmes within the respective departments.
1.2.4
Academic focus of the School
The academic focus of the school is informed by the recognition of the scarcity in South Africa
of skills in Mathematical Sciences. The programmes offered in the school are therefore designed
to provide training in various disciplines of mathematical sciences, with the aim of preparing
students for placement in jobs requiring a significant tertiary level maturity in Mathematical
Sciences, and for further training at a higher level in their areas of specializations.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
8
1.3
School Vision & Mission
1.3.1
Vision of the School
The School of Mathematical and Computational Sciences will be a leading school that
offers innovative educational and research programmes in mathematical sciences and their
computational applications.
1.3.2
Mission of the School
In pursuit of its vision, the school will:
• provide a modern educational environment supported by appropriate technology for
instruction and research;
• design innovative programmes in teaching and research that will produce highly skilled
graduates;
• have a caring approach to the teaching of mathematical sciences courses and
• create an environment to engage in solving real-world problems and societal challenges;
1.4
School Rules
General
Students should note that on registration to study at Walter Sisulu University, they automatically
become members of the University and agree to abide by the rules and regulations of Walter
Sisulu University as amended from time to time and for which further details are available in
the general University prospectus.
Class Attendance
•
•
•
All lectures, including tutorials and laboratory work are compulsory.
Students should at all times be punctual in attending classes.
Lecturers will keep a register of Class Attendance by students, which may be used as part
of the assessment of student performance.
Semester Tests, Lab Work and Handing in of Assignments
•
•
•
Students who are absent from semester assessments or who fail to submit assessments
before or on the due date, will receive a zero mark for that assessment.
If the lecturer is provided with a signed certificate within 7 days after the assessment from
a medical practitioner to confirm that he/she was ill and/or incapacitated the assessment
will be re-administered.
Major semester assessments missed will be re-administered by departmental arrangement.
Course Evaluation
Students will be required to complete Evaluation forms on Course Offering & Lecturer for each
courses at the end of the course.
9
2014
PROSPECTUS
Code of Conduct
The following code of conduct forms part of the way the work within the school is envisaged:
• That the main focus is for students to study & learn;
• that the lecturer and students will take joint responsibility in ensuring that classes are
conducted in an environment conducive to learning;
• to promote such a learning environment the students & lecturer;
• undertake to be respectful to lecturers and other students;
• commit themselves to perform the work in a diligent and responsible manner;
• understand that students are encouraged to ask questions and get feedback;
• undertake to be punctual in attendance of all learning/teaching activities;
• undertake to keep venues clean & tidy and agree not to eat or litter inside the classroom
and
• undertake to take care of the documentation & equipment issued and of the equipment
that are used in practicals or in the classroom.
1.5
Minimum Admission Requirements (for the regular programmes)
National Senior Certificate
Minimum Accumulated Required NSC Subjects
Point Score
29
• Eligibility for admission to a Bachelor’s degree programme
• Achievement rating of at least level 4 (50% – 59%) in
Mathematics, Physical Sciences, English and two other subjects.
Senior Certificate
Symbol D in Mathematics and Physical Science at Standard Grade or Symbol E in Mathematics
and Physical Science at Higher Grade, Exemption for University entrance.
FET Colleges
National Certificate: A certificate with C-symbols for at least four subjects including
Mathematics, Physical Sciences and language requirements for the Senior Certificate.
Recognition of prior learning (RPL)
RPL may be used to demonstrate competence for admission to this programme. This
qualification may be achieved in part through RPL processes. Credits achieved by RPL must
not exceed 50% of the total credits and must not include credits at the exit level.
INTERNATIONAL STUDENTS
Applications from international students are considered in terms of institutional equivalence
reference document submission of international qualification to SAQA for benchmarking in
terms of HEQF.
MATURE AGE ENDORSEMENT
As per General Prospectus Rule G1.6.
National Certificate (Vocational) Level 4
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
10
•
•
•
•
Must meet NC(V) Level 4 statutory requirements
Must obtain 60% in English, Mathematics (not Mathematics
Literacy), Life Orientation
Must obtain 70% for the following compulsory vocational
modules :
Systems Analysis and Design, Data Communication and
Networking, Computer Programming, Physical Science
1.5.1 Selection Criteria for New Students
Selection of new students will be based on scores in Mathematics, English and Physical Science.
Students with scores in these subjects higher than the minimum requirements will be selected
into the programme. Students who are not selected into this programme may be offered places
in the extended programme if they meet the admission requirements there.
1.6 Minimum Admission Requirements and Programme Characteristics (for the
extended programmes)
Name of BSc (Extended Programme)
Programme
Minimum
number
of 480
credits
Delivery Site(s)
NMD
Duration of
A minimum of four years of fulltime study
Programme
Programme Outcomes
Critical Outcomes
The learner will be able to:
Understand the main mathematical concepts and techniques.
Develop a culture of critical and analytical thinking that may
be required in problem solving including the mathematical
modeling and formulation of real-world problems.
Accreditation & Quality Assurance
Vocational Outcomes
After the successful completion of the programme the learner
will be able to utilize the acquired skills in various disciplines
such as Science and Engineering, Economic Sciences, Social
Sciences and Humanities.
CHE, HEQC & SAQA accredited
11
2014
PROSPECTUS
Admission
Requirements
1. Matriculation:National Senior Certificate: Same as for the regular
programme.
OR
Senior Secondary School Certificate: Same as for the
regular programme.
2. Standardized Assessment Test for Access and Placement
(SATAP): The candidate is tested in Mathematics, Science
& English. The tests scores may be used for access and
placement.
Progression Rules
• Refer to Section 1.7.2.1. below.
Graduation Requirements In order to meet the minimum requirements to complete the
Programme the following criteria must be satisfied:
• Complete all core modules at all levels and permitted
electives with a total value of at least 480 credits. Each
fulltime study-year should comprise a minimum of 120
credits.
• The minimum number of credits that must be completed
at Walter Sisulu University must not be less than 50% of
the total number of credits required for the completion of
the programme. All core modules at level three must be
completed at Walter Sisulu University.
1.7
Programme Rules (Undergraduate)
In order to be allowed to proceed to the next level, the following criteria must be satisfied:
• All core modules must be passed at the current level.
1.7.1
Admission Rules
Admission into the programme is contingent upon:
• Meeting the minimum requirements for admission to the programme;
• selection into the programme, (selection is limited by enrolment limits);
• Further,
• admission is on a first come first served basis for students who qualify in terms of selection
criteria;
• not more than 50% of the credits from other institutions will be recognised and
• all exit level courses will only be exempted under extraneous conditions.
See also General Prospectus Rules.
1.7.2 Progression Rules
1.7.2.1 Re-Admission of Continuing Students
•
Students should take note of the Institutional rules G7-G11 on re-admission of students to
undergraduate programme. As provided under institutional rules G8.1, 8.2, 9.1 & 9.2, the
school has set the following criteria for re-admission.
• A student that progresses at a slower rate set out below, will be refused further reSCHOOL OF MATHEMATICAL AND
12
COMPUTATIONAL SCIENCES
admission on the grounds of “poor academic performance’’.
3 Year B Sc (mainstream)
At the end of academic period(year)
1
2
3
4
5
Minimum credits students must have obtained
72
144
216
288
360
4 Year B Sc (extended programme)
At the end of academic period(year)
1
2
3
4
5
6
Minimum credits students must have obtained
80
160
240
320
400
480
•
A student who completes all core modules and pre requisite modules will progress from
one level to the next.
1.7.3
Exit Rules
1.7.3.1 Completion Rules
•
•
•
•
All courses and modules in the curriculum must be completed.
A minimum of 120 credits must be earned at each level of the curriculum.
A minimum total of 360 credits must be completed for the three year programs.
A minimum total of 480 credits must be completed for the four year programs.
1.7.3.2 Exclusion Rules
Refer to Section 1.7.2.1.
1.8
Programme Rules (Honours)
1.8.1
Admission Rules
Admission into the programme is contingent upon:
• Meeting the minimum requirements for admission to the programme;
• selection into the programme, (selection is limited by enrolment limits);
• Further, admission is on a first come first served basis for students who qualify in terms of
selection criteria.
See also General Prospectus Rules.
1.8.2 Progression Rules
1.8.2.1 Re-Admission of Continuing Students
•
•
Refer to the institutional rules on re-admission of students previously admitted as contained
in the revised examination policy and the institution prospectus.
A student who fails the same course twice is not allowed to re-register for the same course.
13
2014
PROSPECTUS
1.8.3
Exit Rules
1.8.3.1 Completion Rules
All courses and modules in the curriculum must be completed.
A minimum of 120 credits must be earned at each level of the curriculum.
1.8.3.2 Exclusion Rules
The maximum period for the degree programme is three years. See also Rules in the General
Prospectus.
1.9
Departments and Programmes
1.9.1
Department of Applied Mathematics
1.9.1.1 Information about Department
Applied mathematics is in a sense the cornerstone of modern science as it is concerned with the
use of mathematical techniques to solve real-world problems. Consistent with this philosophy,
the BSc programme offered in the Department of Applied Mathematics is designed to provide
the necessary foundation in mathematics and to introduce students to the application of
mathematics in the modeling and solution of real-world problems. More information on the BSc
programme is presented below.
Department
Programmes offered
Applied Mathematics
Applied Mathematics
Applied Mathematics
BSc Applied Mathematics - ECP
BSc Applied Mathematics
MSc
Duration
(Full-time)
4
3
2
Delivery Sites
NMD
NMD
NMD
1.9.1.2 Mission of the Department
The mission of the Department of Applied Mathematics includes:
• Creating a mathematically rich environment for the development of sufficiently sophisticated
scientists, engineers and teachers of mathematics;
• conducting and promoting research that addresses the local, regional as well as national
priorities;
• popularizing mathematics through innovative teaching methods and constant
communication with other interfacing departments and
• continually streamlining our programmes to align them with the demands of industry and
commerce.
1.9.1.3 Goals of the Department
The goals of the Department of Applied Mathematics are:
• To produce quality graduates capable of dynamic participation in the economic and
environmental development of the region and beyond;
• to work closely with our community and attempt to solve some of their problems and
SCHOOL OF MATHEMATICAL AND
14
COMPUTATIONAL SCIENCES
•
ensure that the programmes are always relevant to their needs and
through a commitment to service excellence, staff development and the maximum use
of human and other resources, the Department of Applied Mathematics strives to unite
students, staff and employers in the common goal of improving the quality of life of our
community.
•
1.9.1.4 Student Societies in the Department
Science Students Society
1.9.1.5 Programmes In The Department
1.9.1.5.1
BSc Applied Mathematics
1.9.1.5.1.1
Entrepeneurship & Professional Development of Students
Mathematics is a scarce skill in South Africa and is crucial to the scientific and technological
development that leads to economic development of the country. In view of this, the long term
plan of the department envisages the establishment of a linkage between the department and
industry and commerce.
1.9.1.5.1.2
Career Opportunities
A Bachelor of Science degree in Applied Mathematics will prepare the student for jobs in
statistics, actuarial sciences, mathematical modelling, cryptography, for teaching, as well as
postgraduate training leading to a research career in a discipline of Mathematical Sciences.
A strong background in Applied Mathematics is also necessary for research in many areas of
computer science, social science, and engineering.
1.9.1.5.1.3
Purpose of Qualification
To provide basic mathematical knowledge tailored for application in the solution of technical
problems in the marketplace, and for further training at a higher level in various specializations
of Mathematical Sciences.
1.9.1.5.1.4
Exit Level Outcomes of the Programme
A BSc Applied Mathematics graduate should:
• Demonstrate knowledge and understanding of basic concepts and principles in mathematics;
• have a sound mathematical base for further training in mathematics and/or other fields of
study that require a mathematical foundation;
• develop a culture of critical and analytical thinking and be able to apply scientific reasoning
to societal issues;
• demonstrate ability to write mathematics correctly;
• be able to manage and organize own learning activities responsibly and
• be able to demonstrate ability to solve mathematical problems.
15
2014
PROSPECTUS
1.9.1.5.1.5
Programme Characteristics
1.9.1.5.1.5.1
Academic and Research Orientated Study
The degree programme is designed to provide basic mathematical knowledge tailored for
application in the solution of technical problems in the marketplace, and for further training at a
higher level in various specializations of mathematical sciences. The courses in this programme
are developed co-operatively using inputs from internal and external academic sources on a
continuous basis.
1.9.1.5.1.5.2
Practical Work
Practical work in tutorials and computer laboratories provides the practical experience and the
development of computing and research skills that will form the base for future work, academic
and research engagement.
1.9.1.5.1.5.3
Teaching and Learning Methodology
Learning activities include lectures, tutorials, practicals in which independent study are
integrated.
1.9.1.5.1.6
Programme Information
The entire programme is designed to consist of at least 50% of the credits from Mathematics
and/or Applied Mathematics. See Section 1.5 for the Minimum Admission Requirements and
Section 1.7 for Programme Rules.
1.9.1.5.1.6.1
Curriculum
Student must take all the Core modules and Foundational modules at each level. Relevant
electives for which the student has the required pre-requisites must then be chosen so that the
student has a minimum of 120 credits at each level. However, no student may register for more
than 128 credits in any given academic year.
1.9.1.5.1.6.1.1 Core and Foundation Modules
Level 1
Module Name
Core Modules
Precalculus & Calculus I
Introduction to Linear & Vector Alg.
Precalculus & Calculus II
Linear Programming & Applied Computing
Foundation Modules
Computer Literacy
Communication Skills
Total core credits
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
16
Code
Credits
Semester
MAT1101
16
1
APM1101
MAT1201
APM1201
16
16
16
1
2
2
CLT1101
EDU1001
8
8
80
1
1
1&2
Electives required
Total credits
Level 2
Module Name
Multivariate Calculus
Ordinary Differential Equations
Numerical Analysis I
Real Analysis I
Linear Algebra I
Eigenvalue Problems and Fourier Analysis
Total core credits
Electives required
Total credits
Level 3
Module Name
Numerical Methods
Complex Analysis
Mathematical Programming
Linear Algebra II
Total core credits
Electives required
Total credits
40
120
1&2
1&2
Code
MAT2101
MAT2201
APM2101
MAT2102
MAT2202
APM2201
Credits
8
8
16
8
8
16
64
56
120
Semester
1
1
1
2
2
2
1&2
1&2
1&2
Code
APM3101
MAT3202
APM3201
MAT3102
Credits
16
16
16
16
64
56
120
Semester
1
2
2
1
1&2
1&2
1&2
Code
CHE1101
CSI1101
CSI1102
PHY1101
STA1101
CHE1201
CSI1201
PHY1202
STA1202
Credits
16
8
8
16
16
16
8
16
16
Semester
First
First
First
First
First
Second
Second
Second
Second
Code
APM2202
CHE2102
CHE2105
CSI2101
Credits
16
16
16
14
Semester
2
1
First
First
1.9.1.5.1.6.1.2 Electives
Level 1
Module Name
General Chemistry I
Information Systems and Applications
Problem Solving and Programming
General Physics I
Probability & Distribution Theory I
General Chemistry I
Problem Solving and Programming
General Physics II
Probability & Statistical Inference I
Level 2
Module Name
Mechanics I
Analytical Chemistry II
Physical Chemistry II
Programming in JAVA
17
2014
PROSPECTUS
Mechanics & Waves
Probability & Distribution Theory II
Inorganic Chemistry II
Organic Chemistry II
Thermodynamics and Modern Physics
Operating Systems
Statistical Inference II
Level 3
Module Name
Inorganic Chemistry III
Organic Chemistry III
Introduction to Artificial Intelligence
Software Engineering I
Electromagnetism and Quantum Mechanics
Linear Models
Analytical Chemistry III
Physical Chemistry III
Environmental Chemistry – 2003
Data Management
Software Engineering II
Statistical Mechanics and Solid State Physics
Sampling Theory
PHY2101
STA2101
CHE2203
CHE2204
PHY2202
CSI2201
STA2202
16
16
16
16
16
14
16
First
First
Second
Second
Second
Second
Second
Code
CHE3103
CHE3104
CSI3101
CSI3102
PHY3101
STA3101
CHE3202
CHE3205
CHE3207
CSI3201
CSI3202
PHY3202
STA3203
Credits
16
8
14
14
24
16
16
16
12
14
14
24
16
Semester
First
First
First
First
First
First
Second
Second
Second
Second
Second
Second
Second
1.9.1.5.1.6.1.3 Pre-Requisite Courses
Code
MAT2101
Course Name
Level I Precalculus & Calculus I
Introduction to Linear & Vector Alg.
Precalculus & Calculus II
Linear Programming & Applied
Computing
Level II Multivariate Calculus
MAT2201
Ordinary Differential Equations
APM2101
Numerical Analysis I
MAT2102
Real Analysis I
MAT2202
Linear Algebra I
MAT1101
APM1101
MAT1201
APM1201
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
18
Pre-Requisite
FACULTY
FACULTY
FACULTY
FACULTY
admission
admission
admission
admission
requirements
requirements
requirements
requirements
Precalculus & Calculus I, Precalculus
Calculus II
Precalculus & Calculus I, Precalculus
Calculus II
All Level I APM courses, MAT1101,
MAT1201
Precalculus & Calculus I, Precalculus
Calculus II
Precalculus & Calculus I, Precalculus
Calculus II
&
&
&
&
APM2201
MAT3101
Eigenvalue Problems and Fourier
Analysis
Mechanics I
Level III Real Analysis II
MAT3102
Linear Algebra II
APM3101
MAT3201
Numerical Methods
Abstract Algebra
MAT3202
Complex Analysis
APM3201
Mathematical Programming
APM2202
1.9.1.5.1.6.2
All Level I APM courses , MAT1101,
MAT1201, MAT2201
All Level I APM courses, MAT2101
Multivariate Calculus,
Linear Algebra I
Multivariate Calculus,
Linear Algebra I
APM2101, APM2201
Multivariate Calculus,
Linear Algebra I
Multivariate Calculus,
Linear Algebra I
APM2101, APM2201
Real Analysis I,
Real Analysis I,
Real Analysis I,
Real Analysis I,
Award of Qualification
The qualification will be awarded after the satisfaction of the programme requirements,
including completion of 360 credits with a minimum of 120 credits obtained at each level. See
also Rule G12 of the General Prospectus.
1.9.1.5.1.6.3
Programme Tuition Fees
Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition
fees, application fees, registration fees, late registration-fees and other student fees.
1.9.1.5.1.6.4
Articulation
Vertical
Vertical Articulation is possible with: BSc Hons Mathematics and BSc Hons Applied Mathematics,
NQF Level 8
Horizontal
Within WSU
Horizontal Articulation is possible with NQF Level 7 qualifications offered by WSU, e.g. BSc
Applied Statistical Science.
Other Universities
Horizontal Articulation is possible with NQF Level 7 qualifications offered by other institutions,
subject to the relevant institution’s admission requirements.
19
2014
PROSPECTUS
1.9.1.5.1.6.5
Core Syllabi of Courses Offered
APM1101: Introduction to Linear and Vector Algebra
Module Code
APM1101
Lectures per week
Module Name NQF Level
Credits
5
16
Pracs per week Tutorials per week Number of weeks
4 x 50 min
Content / Syllabus
Assessment
1 x 100 min
Semester
1
Notional
hours
13
Iantroduction to Systems of Linear Equations, Gaussian Elimination,
Matrices and Matrix Operations, Inverses Systems of Equations and
Invertibility, Determinant, Cramer’s rule, Eigenvalues and Eigenvectors,
LU-Decomposition, Cryptography, Sets and Set Operations, The
Fundamental Counting Principle, Permutations, Combinations, The
Binomial Theorem, Basic Concepts of Probability, Probability Models,
Vectors and Vector Operations, The Dot Product, The Cross Product,
Applications to Mechanics. Laboratory Work on Vectors and Linear
Algebra with MATLAB.
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
APM1201: Linear Programming
Module Code
APM1201
Lectures per week
Module Name
Pracs per week
4 x 50 min
Content / Syllabus
Assessment
NQF Level
Credits
5
16
Tutorials per week Number of weeks
1 x 100 min
Semester
2
Notional
hours
13
Boolean Algebra: Introduction Two-Terminal Circuit Series-Parallel and
Bridge Circuits Postulates of Switching Circuits Boolean Identities Identity
Elements, Inverses and Cancellations. Linear programming: Introduction,
LP Models, The Diet Problem, The Work-Scheduling Problem, A Capital
Budgeting Problem, Short-term Financial Planning, Blending Problems,
Production Process Models, Multi-period Decision Problems: An Inventory
Model, Multi-period Financial Models, Multi-period Work Scheduling, The
Graphical Method, The Simplex Method – Maximization, The Simplex
Method – The Dual, The Simplex Method – Mixed Constraints
Applied computing. Introduction to MATLAB. Laboratory Work with
MATLAB involving manipulating Matrices, Linear Algebra, Linear
Programming.
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
20
APM2101: Numerical Analysis I
Module Code
APM2101
Lectures per week
Module Name
Pracs per week
4 x 50 min
Content / Syllabus
Assessment
NQF Level
Credits
6
16
Tutorials per week Number of weeks
1 x 100 min
Semester
1
Notional
hours
13
Introduction to numerical analysis: Iterative Methods, Programming
with MATLAB, Interpolation and polynomial approximation: Difference
Operators, Constructing Difference Tables using MATLAB, Lagrange
Polynomial Interpolation, Hermite Interpolation, Divided Differences,
Hermite Revisited, Error Estimation, Numerical differentiation and
integration: Differentiation, integration, Newton-Cotes Formulae,
Composite Integration. Initial value problems, Existence Theorem, Euler
Method, Higher Order Taylor Methods, Runge-Kutta Methods, Midpoint
Rule, Higher Order R-K Methods, Multistep Methods, Adams-Bashforth
Technique, Adams-Moulton Technique, Predictor Corrector Method
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
APM2201: Eigen-Value Problems and Fourier Analysis
Module Code
Module Name
APM2201
Lectures per week Pracs per week
4 x 50 min
NQF Level
6
Tutorials per week
1 x 100 min
Credits
Semester
16
1
Number of weeks Notional hours
13
Content / Syllabus Fourier Series: Orthogonality & Normality (Orthonomality) of trigonometric
functions, Odd & Even functions, Trigonometric series: Full range & Half
range Fourier Series, Parseval Identity. Partial Differential Equations: How
initial & boundary value problem relate to (PDEs),Wave Equation, Heat
Equation, Laplace Equation, How the separation of variables technique
leads (in the simplest examples) to Fourier Series. Eigenvalue Problems:
Sturm-Liouville Equation eigenfuctions & corresponding eigenvalues
of Sturm-Liouville problem, Sturm-Liouville problem for equation
y”+ly = 0 (eigenvalues & eigenfunctions), Orthogonality of SturmLiouville eigenfunctions, Series solution Ordinary Differential Equations:
Bessel, Legendre, Hermite and associated functions, Solution of Bessell
Equation, recurrence relations, Solution of Legendre equation: Legendre
polynomials & Rodrigues formulae, Green formulae and application to
Laplace equation, Vibration of rectangular & circular membrane, Fourier
integral & transformation
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
21
2014
PROSPECTUS
APM2202: Mechanics I
Module Code
APM2202
Lectures per week
Module Name
Mechanics I
Pracs per week
4 x 50 min
Content / Syllabus
Assessment
NQF Level
Credits
Semester
6
16
1
Tutorials per week Number of weeks N o t i o n a l
hours
1 x 100 min
13
Particle kinematics in three dimensions. Curvilinear coordinates;
spherical and cylindrical. Newton’s law of motion. Conservation of energy.
Gravitational and potential theory. Conservation of linear momentum.
Collisions. Conservation of angular momentum. Central forces and
planetary motion.
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
APM3101: Numerical Methods
Module Code
APM3101
Lectures per week
Module Name
Pracs per week
4 x 50 min
Content / Syllabus
Assessment
NQF Level
7
Tutorials per week
1 x 100 min
Credits
Semester
16
1
Number of weeks N o t i o n a l
hours
13
Laplace & Poisson equations: Elliptic, Heat equations-Parabolic, Wave
equations-Hyperbolic. Finite difference method: Replacement of partial
derivatives in a given equation by corresponding finite difference
quotients. Further treatment of the patterns lead us to: Gauss-Seidel
Method for Elliptic case. Crank Nicholson Method for Parabolic equations.
Present Numerical Method for Parabolic equations. The Finite Element
Method (introduction).
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
APM3201: Mathematical Programming
Module Code
Module Name
APM3201
Lectures per week Pracs per week
NQF Level
7
Tutorials per week
Credits
16
Number of weeks
4 x 50 min
1x 100 min
13
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
22
Semester
2
Notional
hours
Content / Syllabus Linear programming: Basic ideas and concepts of program formulation,
Simplex method, Dual problem solution & its relation to the primal.
Nonlinear programming (NLP) background involves classification of
problems/programs according to: Minimization of unconstrained NLPs,
Linearly constrained NLPs that include a special subclass of quadratic
programs concerned with minimization of quadratic functions, Objective
function having appropriate convexity property. Solution Methods:
Lagrangian function with associated multipliers and conditions, KuhnTucker conditions for inequality constrained minimization problems.
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
1.9.1.5.2
BSc Applied Mathematics (Extended Programme):BSCEA
The first 2 years of the BSc Applied Mathematics (Extended Programme) are equivalent to
the first year of the BSc Applied Mathematics programme. In the last two years of the BSc
Applied Mathematics (Extended Programme) the students follow the BSc Applied Mathematics
programme from second year.
At each of the years, 1, 2, 3 & 4, a student must accumulate at least 120 credits towards the
total graduation credits. All the core modules (and foundation modules in the case of Level 1)
must be taken at each Level. The remaining credits to satisfy the credit requirements at the
respective level must be accumulated from the electives.
See Section 1.6 for Admission Requirements and Programme and Characteristics.
1.9.1.5.2.1
1.9.1.5.2.1.1
Curriculum
Core and Foundation Modules
Level 1a (BSCEA)
Module Name
Core
Mathematical Methods I
Mathematical Methods II
Integrated Mathematics I
Integrated Mathematics II
Foundation
Computer Science Fundamentals
Academic Literacy I
Introduction to Programming I
Academic Literacy II
Life Skills
Level 1b ( BSCEA)
Module Name
Core
Mathematical Methods III
Code
Credits
Semester
APM1111
APM1212
MAT1111
MAT1212
16
16
16
16
1
2
1
2
CSI1111
ACL1111
CSI1212
ACL1212
LSK1012
16
8
16
8
8
1
1
2
2
2
Code
Credits
Semester
APM1113
16
1
23
2014
PROSPECTUS
Mathematical Methods IV
APM1214
Integrated Mathematics III
MAT1113
Integrated Mathematics IV
MAT1214
Foundation
Introduction to Computer Architecture
CSI1113
Introduction to Programming II
CSI1214
Total core credits
Electives required
Total credits
Level 3 – same as level 2 of BSc 3 year programme
Module Name
Code
Multivariate Calculus
MAT2101
Ordinary Differential Equations
MAT2201
Numerical Analysis I
APM2101
Real Analysis I
MAT2102
Linear Algebra I
MAT2202
Eigenvalue Problems and Fourier Analysis APM2201
Total core credits
Electives required
Total credits
Level 4 – same as level 3 of BSc 3 year programme
Module Name
Code
Numerical Methods
APM3101
Complex Analysis
MAT3202
Mathematical Programming
APM3201
Linear Algebra II
MAT3102
Total core credits
Electives required
Total credits
1.9.1.5.2.1.2
16
16
16
2
1
2
16
16
96
24
120
1
2
1&2
1&2
1&2
Credits
8
8
16
8
8
16
64
56
120
Semester
1
1
1
2
2
2
1&2
1&2
1&2
Credits
16
16
16
16
64
56
120
Semester
1
2
2
1
1&2
1&2
1&2
Electives
Level 1a (BSCEA) – An elective cannot be taken, presently, at this year because
of exceeding credits
Module Name
Code
Credits
Semester
Extended General Chemistry I
CHE1111
16
1
Extended General Physics II
PHY1212
16
2
Extended Organic and Physical Chemistry I
CHE1212
16
2
Level 1b (BSCEA)
Extended General Physics III
PHY1113
16
1
Extended General Chemistry II
CHE1113
16
1
Probability & Distribution theory I
STA1101
16
1
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
24
Extended General Physics IV
Extended Organic and Physical Chemistry II
Statistical Inference I
1.9.1.5.2.1.3
Course Code
APM1111
APM1212
APM1113
APM1214
MAT1111
MAT1212
MAT1113
MAT1214
1.9.1.5.2.2
PHY1214
CHE1214
STA1202
16
16
16
2
2
2
Pre-Requisite Courses
Course Name
Mathematical Methods I
Mathematical Methods II
Mathematical Methods III
Mathematical Methods IV
Integrated Mathematics I
Integrated Mathematics II
Integrated Mathematics III
Integrated Mathematics IV
Pre-Requisite
Faculty admission requirements
Faculty admission requirements
Faculty admission requirements
Faculty admission requirements
Faculty admission requirements
FACULTY admission requirements
MAT1111
MAT1212
Award of Qualification
The qualification will be awarded after the satisfaction of the programme requirements,
including completion of 360 credits with a minimum of 120 credits obtained at each level. See
also Rule G12 of the General Prospectus.
1.9.1.5.2.3
Programme Tuition Fees
Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition
fees, application fees, registration fees, late registration-fees and other student fees.
1.9.1.5.2.4
Articulation
Vertical
Vertical Articulation is possible with: BSc Hons Mathematics and BSc Hons Applied
Mathematics, NQF Level 8
Horizontal
Within WSU
Horizontal Articulation is possible with NQF Level 7 qualifications offered by WSU, e.g. BSc
Applied Statistical Science.
Other Universities
Horizontal Articulation is possible with NQF Level 7 qualifications offered by other
institutions, subject to the relevant institution’s admission requirements.
25
2014
PROSPECTUS
1.9.1.5.2.5
Core Syllabi of Courses Offered
APM1111: Mathematical Methods I
Module Code
Module
Name
APM1111
Lectures per week
2 x 50 min
5
16
1
Pracs per week Tutorials per week Number of weeks Notional hours
0
1 x 50 min
13
160
Content / Syllabus
Coordinate Systems: Review of Coordinate Systems in 2 and 3 dimensions
Vectors: Introduction to vectors, Vector Operations, The Dot Product,
The Cross Product, Applications to Coordinate Geometry and Mechanics
Laboratory Work on Vectors with MATLAB
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
Assessment
NQF Level
Credits
Semester
APM1212: Mathematical Methods II
Module Code
Module Name NQF Level
Credits
Semester
APM1212
5
16
2
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
0
1 x 50 min
13
160
Content / Syllabus Matrix Theory: Matrices and Matrix Operations, Determinants, Inverses.
Systems of Linear Equations: Introduction to Systems of Linear Equations,
Gaussian Elimination, Gauss-Jordan Elimination, Systems of Equations
and Invertibility,
Laboratory Work on Linear Algebra with MATLAB
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
APM1113: Mathematical Methods III
Module Code
Module Name NQF Level
Credits
Semester
APM1113
5
16
2
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
0
1 x 50 min
13
160
Content / Syllabus Sets: Set Operations, De Morgan’s laws, Power Set, Cartesian Products,
Indexed Families of Sets, Laws of Algebra of Sets
The Fundamental Counting Principle, Permutations, Combinations, The
Binomial Theorem, The Principle of Mathematical Induction.
Logic: Logical Operations and Truth Tables, Tautologies and Contradictions,
Logical Equivalence.
Boolean algebra: Boolean Polynomials, Introduction to Two-Terminal
Circuit Series-Parallel and Bridge Circuits, Postulates of Switching Circuits,
Boolean Identities, Identity Elements, Inverses, and Cancellations.
Laboratory Work on Discreet Mathematics with MATLAB
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
26
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
APM1214: Mathematical Methods IV
Module Code
Module Name NQF Level
Credits
APM1214
5
16
Lectures per week Pracs per week Tutorials per week Number of weeks
2 x 50 min
0
1 x 50 min
13
Content/ Syllabus
Assessment
1.9.2
Semester
2
Notional hours
160
Linear programming: Introduction, LP Models, The Diet Problem, The
Work- Scheduling Problem, A Capital Budgeting Problem, Short-term
Financial Planning, Blending Problems, Production Process Models,
Multi-period Decision Problems: An Inventory Model, Multi-period
Financial Models, Multi-period Work Scheduling, The Graphical Method,
The Simplex Method – Maximisation, The Simplex Method – The Dual,
The Simplex Method – Mixed Constraints
Laboratory Work on Linear Programming with MATLAB
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
Department of Mathematics
1.9.2.1 Information about Department
The Department of Mathematics strives towards improving its leadership role in the training of
mathematicians who will contribute to the development of the country. It promotes excellence
in appropriate research and offers career orientated degree programmes.
The Department offers programmes at the Mthatha Campus (Nelson Mandela Drive delivery
site), and service courses at three campuses (Mthatha, Butterworth and Buffalo City) and five
delivery sites (Nelson Mandela Drive, Ibika, Potsdam, Chiselhurst and College Street).
The following is a summary of programmes that are offered by the Department of Mathematics.
Department
Department of
Mathematics
1.9.2.2
Programmes offered
BSc Mathematics (ECP)-BSCME
BSc Mathematics-BSCM
BSc Hons Mathematics-BSM
MSc Mathematics
Duration
4yrs
3yrs
1yrs
2yrs
Delivery Sites
NMD
NMD
NMD
NMD
Mission of the Department
The mission of the Department of Mathematics includes:
• Creating mathematically rich environment for the development of sufficiently sophisticated
scientists, engineers and teachers of mathematics.
• Conducting and promoting research that addresses the local, regional as well as national
27
2014
PROSPECTUS
•
•
priorities.
Popularizing mathematics through innovative teaching methods and constant communication
with other interfacing departments.
Continually streamlining our programmes to align them with the demands of industry and
commerce.
1.9.2.3
Goals of the Department
The goals of the Department of Mathematics are:
• To produce quality graduates capable of dynamic participation in the economic and
environmental development of the region and beyond.
• Working closely with our community attempt to solve some of the problems and ensure
that the programmes are always relevant to their needs.
• Through a commitment to service excellence, staff development and the maximum use
of human and other resources, the Department of Mathematics strives to unite students,
staff and employers in the common goal of improving the quality of life of our community.
1.9.2.4
Student Societies in the Department
Science students society
1.9.2.5
Programmes in the Department
1.9.2.5.1
BSc Mathematics (BSCM)
1.9.2.5.1.1
Entrepeneurship & Professional Development of Students
Mathematics is a scarce skill in South Africa and is crucial to the scientific and technological
development that leads to economic development of the country. In view of this, the long term
plan of the department envisages the establishment of a linkage between the department and
industry and commerce.
1.9.2.5.1.2
Career Opportunities
A Bachelor of Science degree in mathematics will prepare the student for jobs in statistics,
actuarial sciences, mathematical modeling, and cryptography; for teaching; as well as
postgraduate training leading to a research career in mathematics. A strong background in
mathematics is also necessary for research in many areas of computer science, social science,
and engineering
1.9.2.5.1.3
Purpose of Qualification
To provide basic mathematical knowledge needed for placement in jobs requiring a significant
amount of mathematical maturity, and for further training at a higher level in various
specializations of mathematics.
1.9.2.5.1.4
Exit Level Outcomes of the Programme
A BSc Applied Mathematics graduate should:
• demonstrate knowledge and understanding of basic concepts and principles in mathematics,
• have a sound mathematical basis for further training in mathematics and/or other fields of
study that require a mathematical foundation,
• develop a culture of critical and analytical thinking and be able to apply scientific reasoning
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
28
•
•
to societal issues,
demonstrate ability to write mathematics correctly,
be able to manage and organize own learning activities responsibly, be able to demonstrate
ability to solve mathematical problems.
•
1.9.2.5.1.5
Programme Characteristics
1.9.2.5.1.5.1
Academic and Research Orientated
The programme is mainly academic and research orientated because academic study is
combined with related practical work aimed at developing more conceptual mathematical than
computational outcomes. The courses in this programme are developed co-operatively using
inputs from internal and external academic sources on a continuous basis.
1.9.2.5.1.5.2
Practical Work
Practical work in tutorials and computer laboratories provides the practical experience and the
development of computing and research skills that will form the basis of future work, academic
and research engagement.
1.9.2.5.1.5.3
Teaching and Learning Methodology
Learning activities include lectures, tutorials, practicals in which in which independent study
are integrated.
1.9.2.5.1.6 Programme Information
The programme is designed to consist of at least 50% of the credits from Mathematics and/or
Applied Mathematics. See Section 1.5 for the Minimum Admission Requirements and Section
1.7 for Programme Rules.
1.9.2.5.1.6.1
Curriculum
1.9.2.5.1.6.1.1 Core and Foundation Modules
Level 1
Module Name
Core
Precalculus & Calculus I
Introduction to Linear & Vector Alg.
Precalculus & Calculus II
Linear Programming & Applied Computing
Foundation
Computer Literacy
Communication Skills
Total credits
Level 2
Module Name
Multivariate Calculus
29
Code
Credits
Semester
MAT1101
APM1101
MAT1201
APM1201
16
16
16
16
First
First
Second
Second
CLT1101
EDU1001
8
8
80
First
First
Code
MAT2101
Credits
8
Semester
First
2014
PROSPECTUS
Ordinary Differential Equations
Numerical Analysis I
Real Analysis I
Linear Algebra I
Eigenvalue Problems and Fourier Analysis
Total credits
Level 3
Module Name
Real Analysis II
Linear Algebra II
Numerical Methods
Abstract Algebra
Complex Analysis
Mathematical Programming
Total credits
MAT2201
APM2101
MAT2102
MAT2202
APM2201
8
16
8
8
16
64
First
First
Second
Second
Second
Code
MAT3101
MAT3102
APM3101
MAT3201
MAT3202
APM3201
Credits
16
16
16
16
16
16
96
Semester
First
First
First
Second
Second
Second
Code
CHE1101
CSI1101
CSI1102
PHY1101
STA1101
CHE1201
CSI1201
PHY1202
STA1202
Credits
16
8
8
16
16
16
8
16
16
40
Semester
First
First
First
First
First
Second
Second
Second
Second
Code
APM2202
CHE2102
CHE2105
CSI2101
PHY2101
STA2101
CHE2203
CHE2204
PHY2202
CSI2201
Credits
16
16
16
14
16
16
16
16
16
14
Semester
Second
First
First
First
First
First
Second
Second
Second
Second
1.9.2.5.1.6.1.2 Electives
Level 1
Module Name
General Chemistry I
Information Systems and Applications
Problem Solving and Programming
General Physics I
Probability & Distribution Theory I
General Chemistry I
Problem Solving and Programming
General Physics II
Probability & Statistical Inference I
Minimum total credits
Level 2
Module Name
Mechanics I
Analytical Chemistry II
Physical Chemistry II
Programming in JAVA
Mechanics & Waves
Probability & Distribution Theory II
Inorganic Chemistry II
Organic Chemistry II
Thermodynamics and Modern Physics
Operating Systems
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
30
Statistical Inference II
Minimum total credits
Level 3
Module Name
Inorganic Chemistry III
Organic Chemistry III
Introduction to Artificial Intelligence
Software Engineering I
Electromagnetism and Quantum Mechanics
Linear Models
Analytical Chemistry III
Physical Chemistry III
Environmental Chemistry – 2003
Data Management
Software Engineering II
Statistical Mechanics and Solid State Physics
Sampling Theory
Minimum total credits
STA2202
16
56
Second
Code
CHE3103
CHE3104
CSI3101
CSI3102
PHY3101
STA3101
CHE3202
CHE3205
CHE3207
CSI3201
CSI3202
PHY3202
STA3203
Credits
16
8
14
14
24
16
16
16
12
14
14
24
16
24
Semester
First
First
First
First
First
First
Second
Second
Second
Second
Second
Second
Second
1.9.2.5.1.6.1.3 Pre-Requisite Courses
Code
Course Name
Level 1
Pre-Requisite
MAT1101
APM1101
MAT1201
APM1201
FACULTY admission requirements
FACULTY admission requirements
FACULTY admission requirements
Introduction to Linear & Vector Algebra
MAT2101
Precalculus & Calculus I
Introduction to Linear & Vector Alg.
Precalculus & Calculus II
Linear Programming & Applied
Computing
Level 2
Multivariate Calculus
MAT2201
Ordinary Differential Equations
APM2101
Numerical Analysis I
MAT2102
Real Analysis I
MAT2202
Linear Algebra I
APM2201
Eigenvalue Problems and Fourier
Analysis
Mechanics I
APM2202
31
Precalculus & Calculus I, Precalculus
Calculus II
Precalculus & Calculus I, Precalculus
Calculus II
All Level I APM courses, MAT1101,
MAT1201
Precalculus & Calculus I, Precalculus
Calculus II
Precalculus & Calculus I, Precalculus
Calculus II
All Level I APM courses , MAT1101,
MAT1201, MAT2201
All Level I APM courses, MAT2101
&
&
&
&
2014
PROSPECTUS
MAT3101
Level 3
Real Analysis II
MAT3102
Linear Algebra II
APM3101
MAT3201
Numerical Methods
Abstract Algebra
MAT3202
Complex Analysis
APM3201
Mathematical Programming
1.9.2.5.1.6.2
Multivariate Calculus,
Linear Algebra I
Multivariate Calculus,
Linear Algebra I
APM2101, APM2201
Multivariate Calculus,
Linear Algebra I
Multivariate Calculus,
Linear Algebra I
APM2101, APM2201
Real Analysis I,
Real Analysis I,
Real Analysis I,
Real Analysis I,
Award of Qualification
The qualification will be awarded after the satisfaction of the programme requirements,
including completion of 360 credits with a minimum of 120 credits obtained at each level. See
also Rule G12 of the General Prospectus.
1.9.2.5.1.6.3
Programme Tuition Fees
Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition
fees, application fees, registration fees, late registration-fees and other student fees.
1.9.2.5.1.6.4
Articulation
Vertical
Vertical Articulation is possible with: BSc Hons Mathematics and BSc Hons Applied Mathematics,
NQF Level 8
Horizontal
Within WSU
Horizontal Articulation is possible with NQF Level 7 qualifications offered by WSU, e.g. BSc
Applied Statistical Science.
Other Universities
Horizontal Articulation is possible with NQF Level 7 qualifications offered by other institutions,
subject to the relevant institution’s admission requirements.
1.9.2.5.1.6.5
Core Syllabi of Courses Offered
MAT1101: Precalculus & Calculus I
Module Code
Module Name NQF Level
Credits
Semester
MAT1101
5
16
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
4 x 50 min
1 x 100 min
13
160
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
32
Content / Syllabus Sets, definitions, examples, operations on sets, complementation and
DeMorgan’s laws. The real number system, graphs of linear, quadratic,
polynomial and rational functions, exponential and logarithmic functions,
trigonometric functions, inequalities. Linear systems. Limits, continuity
and differentiability of functions of a single variable, curve sketching,
maxima and minima, mean value theorems, indeterminate forms.
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT1201: Precalculus & Calculus II
Module Code
Module Name NQF Level
Credits
MAT1201
5
16
Lectures per week Pracs per week Tutorials per week Number of weeks
4 x 50 min
1 x 100 min
13
Semester
1
Notional hours
160
Content / Syllabus Mathematical induction, permutations and combinations, binomial
theorem, complex numbers and polar coordinates. Introduction to
integration, integration of simple functions, fundamental theorem of
integral calculus. Further techniques of integration, introduction to
series and sequences, power series and Taylor polynomials and Taylor’s
theorem, introduction to differential equations (ordinary differential
equations of first order).
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT2101: Multivariate Calculus
Module Code
Module Name NQF Level
Credits
Semester
MAT2101
6
8
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
80
Content / Syllabus Functions of several variables, surfaces, continuity, partial derivatives,
implicit functions, the chain rule, higher order derivatives, Taylor’s theorem,
local extrema and saddle points, multiple integrals, line integrals, Green’s
theorem, Jacobians, spherical and cylindrical coordinates.
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT2102: Real Analysis I
Module Code
Module Name NQF Level
Credits
Semester
MAT2102
6
8
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
80
33
2014
PROSPECTUS
Content / Syllabus Real number system as a complete ordered field, real sequences,
convergent sequences, monotone sequences and monotone convergence
theorem, subsequences, Cauchy sequences and Cauchy’s general
principle of convergence, infinite series and various tests of convergence,
functions on closed intervals.
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT2201: Ordinary Differential Equations
Module Code
Module Name NQF Level
Credits
Semester
MAT2201
6
8
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
80
Content / Syllabus Second order linear differential equations with constant coefficients,
non-homogeneous equations, special methods for particular integrals,
variation of parameters, higher order differential equations, solution in
series, applications.
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT2202: Linear Algebra I
Module Code
Module Name NQF Level
Credits
Semester
MAT2202
6
8
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
80
Content / Syllabus Further properties of matrices and determinants, real vector spaces, basis
and dimension, linear transformations, eigenvalues, diagonalization.
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT3101: Real Analysis II
Module Code
Module Name NQF Level
Credits
MAT3101
7
16
Lectures per week Pracs per week Tutorials per week Number of weeks
2 x 50 min
2 x 50 min
13
Semester
1
Notional hours
160
Content / Syllabus Countable and uncountable sets, topology of real line; open and closed
sets of R and their properties, limit points and the Bolzano - Weirstrass
Theorem for sets, subsequences and the Bolzano - Weierstrass Theorem,
compact sets and the Heine-Borel Theorem, uniform continuity, Riemann
integration, uniform convergence.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
34
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT3102: Linear Algebra II
Module Code
Module
Name
NQF Level
Credits
Semester
MAT3102
7
16
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
2 x 50 min
13
160
Content / Syllabus Inner product spaces, the Cauchy - Schwarz and triangle inequalities,
orthogonality and orthonormal bases, the Gram -Schmidt orthogonalization
process, complex inner product spaces. eigenvalues and eigenvectors,
diagonalization of a matrix, real symmetric matrices, complex eigenvalues,
quadratic forms.
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT3201: Abstract Algebra
Module Code
Module Name NQF Level
Credits
Semester
MAT3201
7
16
2
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
2 x 50 min
13
160
Content / Syllabus Group Theory; definition and examples, elementary properties, subgroups,
cosets, Lagrange’s Theorem. Ring Theory; definitions, elementary
properties, subrings and ideals, integral domains and fields, residue
class rings, polynomial rings, congruences, prime and maximal ideals.
Homomorphism Theorems; factor groups and rings, the Fundamental
homomorphism theorem, embedding theorems.
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT3202: Complex Analysis
Module Code
Module
Name
NQF Level
Credits
Semester
MAT3202
7
16
2
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
2 x 50 min
13
160
Content / Syllabus Functions of a complex variable, limit, continuity and differentiability,
power series, integration, singularities and the calculus of residues,
uniform convergence.
35
2014
PROSPECTUS
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
1.9.2.5.2 BSc Mathematics (Extended Programme): BSCME
The first 2 years of the BSc Mathematics (Extended Programme) are equivalent to the first year
of the BSc Mathematics programme. In the last two years of the BSc Mathematics (Extended
Programme) the students follow the BSc Mathematics programme from second year.
At each of the years, 1, 2, 3 & 4, a student must accumulate at least 120 credits towards the
total graduation credits. All the core modules (and foundation modules in the case of Level 1)
must be taken at each Level. The remaining credits to satisfy the credit requirements at the
respective level must be accumulated from the electives. The following table captures briefly
the admission requirement and programme characteristics.
See also Section 1.6 for Admission Requirements and Programme and Characteristics.
1.9.2.5.2.1
1.9.2.5.2.1.1
Curriculum
Core and Foundation Modules
Level 1a (BSCME)
Module Name
Core
Integrated Mathematics I
Integrated Mathematics II
Foundation
Computer Science Fundamentals
Academic Literacy I
Introduction to Programming I
Academic Literacy II
Life Skills
Level 1b (BSCME)
Module Name
Integrated Mathematics III
Introduction to Linear & Vector Algebra
Integrated Mathematics IV
1.9.2.5.2.1.2
Code
Credits
Semester
MAT1111
MAT1212
16
16
First
Second
CSI1111
ACL1111
CSI1212
ACL1212
LSK1012
16
8
16
8
8
First
First
Second
Second
Second
Code
MAT1113
APM1101
MAT1214
Credits
16
16
16
Semester
First
First
Second
Electives
Level 1a (BSCME)
Module Name
Extended General Physics I
Extended General Chemistry I
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
Code
PHY1111
CHE1111
36
Credits
16
16
Semester
First
First
Extended General Physics II
Extended Organic and Physical Chemistry I
Level 1b (BSCME)
Extended General Physics III
Extended General Chemistry II
Probability & Distribution theory I
Extended General Physics IV
Extended Organic and Physical Chemistry II
Statistical Inference I
1.9.2.5.2.1.3
Code
PHY1212
CHE1212
16
16
Second
Second
PHY1113
CHE1113
STA1101
PHY1214
CHE1214
STA1202
16
16
16
16
16
16
First
First
First
Second
Second
Second
Pre-Requisite Courses
MAT1111
MAT1212
MAT1113
APM1101
Course Name
Level I Integrated Mathematics I
Integrated Mathematics II
Integrated Mathematics III
Linear Programming & Applied Computing
MAT1214
APM1201
Integrated Mathematics IV
Introduction to Linear & Vector Algebra
1.9.2.5.2.2
Pre-Requisite
Faculty admission requirements
FACULTY admission requirements
MAT1111
Introduction to Linear & Vector
Algebra
MAT1212
FACULTY admission requirements
Core Syllabi Of Courses Offered
MAT1111: Integrated Mathematics I
Module Code
Module Name NQF Level
Credits
MAT1111
5
16
Lectures per week Pracs per week Tutorials per week Number of weeks
2 x 50 min
1 x 100 min
13
Semester
1
Notional hours
160
Content / Syllabus Algebraic Expressions: Factorization; Remainder and Factor theorems;
Nature of roots of a quadratic equation; Simplification of rational
expressions; Radicals and Exponents; Change of subject of formula
Sets: Definitions and Examples; Operations on sets; Venn Diagrams
Real Numbers: The Real number system; Inequalities – linear, quadratic,
rational and absolute value; Intervals on the Real line
Functions: Definitions; Ways of representing a function (descriptive,
algebraic, numerical and graphical); Polynomial, Rational, Absolute
value, Exponential and Logarithmic functions; Symmetry; Even and Odd
functions; Inverse of a function
Limits and Continuity: Limit of a function; Standard limits; Limit theorems
(without proof) and their applications; Continuous functions (A geometric
and computational approach, minimizing the rigorous epsilon-delta
approach)
37
2014
PROSPECTUS
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT1212: Integrated Mathematics II
Module Code
Module Name NQF Level
Credits
Semester
MAT1212
5
16
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 100 min
13
160
Content / Syllabus Differentiation, curve sketching, mean value theorems, applications of
derivatives and partial differentiation
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT1113: Integrated Mathematics III
Module Code
Module Name NQF Level
Credits
Semester
MAT1113
5
16
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 100 min
13
160
Content / Syllabus Intergration and its rules, areas, volumes and rotations of curves,
Differential Equations (first order, first degree).
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT1214: Integrated Mathematics IV
Module Code
Module Name NQF Level
Credits
Semester
MAT1214
5
16
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 100 min
13
160
Content / Syllabus Mathematical Induction: Principle of Mathematical Induction and its
applications to standard proofs
Sequences and Series: Arithmetic and Geometric sequences and series;
Power series expansions; Taylor & Maclaurin series; Binomial series
Complex Numbers: Cartesian and Polar co-ordinates and the conversion
from one co-ordinate system to the other; Modulus and Argument; The
Argand plane; De Moivre’s theorem; Euler’s formula
Vectors: Basic concepts; Vector operations; The Dot product and the
Cross product; Application to co-ordinate
Matrices: Definitions and Examples; Algebra of matrices; The Inverse
of a square matrix; The Determinant of a square matrix; Properties of
Determinants
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
38
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
1.9.2.5.3 Honours BSc Mathematics: BSM
1.9.2.5.3.1 Entrepreneurship & Professional Development of Students
Mathematics is a scarce skill in South Africa and is crucial for the scientific and technological
development that leads to economic development of the country. In view of this, the long term
plan of the department envisages the establishment of a linkage between the department,
industry and commerce.
1.9.2.5.3.2
Career Opportunities
A Bachelor of Science Honours degree in mathematics will prepare the student for jobs in
statistical sciences, actuarial sciences, mathematical modeling, and cryptography; for teaching;
as well as postgraduate training leading to a research career in mathematics. A strong
background in mathematics is also necessary for research in many areas of computer science,
social science, and engineering.
1.9.2.5.3.3
Purpose of Qualification
To provide basic mathematical knowledge needed for placement in jobs requiring a significant
amount of mathematical maturity, and for further training at a higher level in various
specializations of mathematics.
1.9.2.5.3.4
Exit Level Outcomes of The Programme
After the successful completion of the programme the student will be able to utilize the acquired
skills in various disciplines such as Science and Engineering, Economic Sciences, Social Sciences
and Humanities.
1.9.2.5.3.5
Programme Characteristics
1.9.2.5.3.5.1
Academic and Research Orientated
The programme is mainly academic and research orientated because academic study is
research based and aimed at developing conceptual mathematical outcomes and training in
new knowledge generation.
1.9.2.5.3.5.2
Practical Work
Research work provides the practical experience and the development of computing and
research skills that will form the basis of future work, academic and research engagement.
1.9.2.5.3.5.3
Teaching and Learning Methodology
Learning activities include lecture, assignments, proposal development, hypothesising research
39
2014
PROSPECTUS
problems, data collection, capturing, analysis, interpretation, report writing, communications
such as conference posters, papers. The programme is accredited with CHE and HEQC.
1.9.2.5.3.6 Programme Information
The entire programme is designed to consist of courses/modules in advanced Mathematics.
1.9.2.5.3.6.1
Minimum Admission Requirements
See Section 1.8 for Admission Requirements and Programme Rules.
1.9.2.5.3.6.2
Selection Criteria for New Students
All applicants will be interviewed for selection into the programme and immediately allocated
supervisors for the research component of the course.
1.9.2.5.3.6.3
Curriculum
1.9.2.5.3.6.3.1 Required Modules
The current Hons programme requires a selection of FOUR courses and a Compulsory Research
Project as given below with the restriction that MAT 4101 cannot be taken concurrently either
with MAT4105 or MAT4107. The total required credits are 126.
Course Code
Course Name
Credits
Pre-Requisite
Algebra
MAT4101
24
Admission
Requirements*
Classical Analysis
MAT4102
24
Admission
Requirements
Functional Analysis
MAT4103
24
Admission
Requirements
General Topology
MAT4104
24
Admission
Requirements
Group Theory
MAT4105
24
Admission
Requirements
Measure Theory
MAT4106
24
Admission
Requirements
Ring Theory
MAT4107
24
Admission
Requirements
Differential Equations MAT4108
24
Admission
Requirements
Research Project
(Compulsory)
30
MAT4109
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
40
1.9.2.5.3.6.3.2 Courses Offered
Level 1
Module Name
Algebra
Classical Analysis
Functional Analysis
General Topology
Group Theory
Measure Theory
Ring Theory
Differential Equations
Research Project (Compulsory)
Code
MAT4101
MAT4102
MAT4103
MAT4104
MAT4105
MAT4106
MAT4107
MAT4108
MAT4109
Credits
24
24
24
24
24
24
24
24
30
Semester
1 and/or 2
1 and/or 2
1 and/or 2
1 and/or 2
1 and/or 2
1 and/or 2
1 and/or 2
1 and/or 2
1 and/or 2
1.9.2.5.3.6.3.3 Pre-Requisite Courses
Course Code
MAT4101
MAT4102
MAT4103
MAT4104
MAT4105
MAT4106
MAT4107
MAT4108
1.9.2.5.3.6.4
Course Name
Algebra
Classical Analysis
Functional Analysis
General Topology
Group Theory
Measure Theory
Ring Theory
Differential Equations
Pre-Requisite
MAT3201
MAT3101
MAT3101
MAT3101
MAT3101, MAT3201
MAT3101
MAT3101, MAT3201
MAT2201
Award of Qualification
The qualification will be awarded after one completes 120 credits.
[also see Rule G12 of the General Prospectus]
1.9.2.5.3.6.5
Programme Tuition Fees
Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition
fees, application fees, registration fees, late registration-fees and other student fees.
1.9.2.5.3.6.6
Articulation
Vertical
Vertical Articulation is possible with: MSc Mathematics, NQF Level 9
Horizontal
Within WSU
Horizontal Articulation is possible with NQF Level 8 qualifications offered by WSU, e.g. BSc
Hons Applied Mathematics, NQF Level 8, subject to the admission requirements of that
qualification.
41
2014
PROSPECTUS
Other Universities
Horizontal Articulation is possible with NQF Level 8 qualifications offered by other institutions,
subject to the relevant institution’s admission requirements.
1.9.2.5.3.6.7
Core Syllabi of Courses Offered
MAT4101: Algebra
Module Code
Module Name NQF Level
Credits
Semester
MAT4101
8
24
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
4 x 50 min
1x 100 min
13
Content / Syllabus Ring theory; the isomorphism theorems, polynomial rings, the division
algorithm, unique factorization domains, euclidean domain, theory
of fields, Galois theory. Group theory; the isomorphism theorems,
permutation groups, Sylow theorems, p-groups.
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT4102: Classical Analysis
Module Code
MAT4102
Module Name NQF Level
8
Credits
24
Semester
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
4 x 50 min
2 x 50 min
13
Content / Syllabus Study of the further properties of a function of a complex variable,
conformal mappings, infinite products, analytic continuation, entire
functions.
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT4103: Functional Analysis
Module Code
MAT4103
Module Name NQF Level
Functional 8
Analysis
Credits
24
Semester
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
4 x 50 min
2 x 50 min
13
Content / Syllabus A brief review of the theory of metric spaces, normed spaces and their
completeness (Banach spaces), linear transformations, Hahn-Banach
theorem, reflexivity, open mapping theorem, closed graph theorem and
the principle of uniform boundedness, basic theory of Hilbert spaces and
finite dimensional spectral theory.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
42
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT4104: General Topology
Module Code
MAT4104
Module Name NQF Level
General
8
Topology
Lectures per week Pracs per week
4 x 50 min
Credits
24
Semester
1
Tutorials per week Number of weeks Notional hours
2 x 50 min
13
Content / Syllabus Topological spaces, metric topology, convergence of sequences and nets
in topological spaces, continuity and homeomorphism, countability and
separation, compactness, connectedness, product topology
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT4105: Group Theory
Module Code
MAT4105
Module
Name
Group Theory
NQF Level
Credits
Semester
8
24
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
Content / Syllabus Isomorphism theorems, permutation groups, Cayley’s theorem, Sylow
theorems, p-groups, classification of finite groups of low order, free
groups, free abelian groups, fundamental theorem of abelian groups,
group representations, the fundamental group in topology.
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT4106: Measure Theory
Module Code
MAT4106
Module Name NQF Level
Measure Theory 8
Lectures per week Pracs per week
4 x 50 min
Credits
24
Semester
1
Tutorials per week Number of weeks Notional hours
2 x 50 min
13
Content / Syllabus Measures; rings and algebras of sets, measures, outer measures, Borel
measures on R, integration; measurable functions, product measures,
the Lebesgue integral, decomposition and differentiation of measures;
signed measures.
43
2014
PROSPECTUS
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT4107: Ring Theory
Module Code
MAT4107
Module Name NQF Level
Ring Theory
8
Credits
24
Semester
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
4 x 50 min
2 x 50 min
13
Content / Syllabus Isomorphism theorems, embedding theorems, polynomial rings, the
division algorithm, unique factorization domains, Euclidean domains,
radical theory in commutative rings, theory of finite fields, Galois theory.
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
MAT4108: Differential Equations
Module Code
MAT4108
Module Name NQF Level
Differential
8
Equations
Credits
24
Semester
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
4 x 50 min
2 x 50 min
13
Content / Syllabus Study of ordinary differential equations, including modeling physical
systems, e.g. predator-prey population models; Analytic methods of
solving ordinary differential equations of first and higher orders: Laplace
Transform methods, series solutions, etc;
Nonlinear autonomous
systems: critical point analysis and phase plane diagrams; Numerical
solution of differential equations;
Introduction to partial differential equations.
Assessment
Semester mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester mark (DP) x
60% + Exam Mark x 40%.
1.9.2.5.4
MSc Mathematics
1.9.2.5.4.1
Entrepreneurship & Professional Development of Students
Mathematics is a scarce skill in South Africa and is crucial to the scientific and technological
development that leads to economic development of the country. In view of this, the long term
plan of the department envisages the establishment of a linkage between the department and
industry and commerce.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
44
1.9.2.5.4.2
Career Opportunities
A Master of Science degree in mathematics will prepare the student for jobs in statistics, actuarial
sciences, mathematical modeling, and cryptography; for teaching; as well as postgraduate
training leading to a research career in mathematics. A strong background in mathematics is
also necessary for research in many areas of computer science, social science, and engineering
1.9.2.5.4.3
Purpose of Qualification
To provide mathematical knowledge needed for placement in jobs requiring a significant amount
of mathematical maturity, and for further training at a higher level in various specializations of
mathematics.
1.9.2.5.4.4
Exit Level Outcomes of The Programme
After the successful completion of the programme the student will be able to utilize the acquired
skills in various disciplines such as Science and Engineering, Economic Sciences, Social Sciences
and Humanities.
1.9.2.5.4.5
Programme Characteristics
1.9.2.5.4.5.1
Academic and Research Orientated
The programme is mainly academic and research orientated because academic study is
research based and aimed at developing conceptual mathematical outcomes and training in
new knowledge generation.
1.9.2.5.4.5.2
Practical Work
Research work provides the practical experience and the development of computing and
research skills that will form the basis of future work, academic and research engagement.
1.9.2.5.4.5.3
Teaching and Learning Methodology
Learning activities include proposal development, hypothesising research problems, data
collection, capturing, analysis, interpretation, report writing, communications such as conference
posters, papers. The programme is accredited with CHE and HEQC.
1.9.2.5.4.6
Programme Information
1.9.2.5.4.6.1
Minimum Admission Requirements
A BSc Honours degree in Mathematics or Applied Mathematics. The department may put
additional requirements.
1.9.2.5.4.6.2
Selection Criteria for New Students
All applicants will be interviewed for selection into the programme and immediately allocated
45
2014
PROSPECTUS
supervisors.
1.9.2.5.4.6.1
Curriculum
Core and Foundation Modules
Year Level
1
1
2
2
Semester
1
2
3
4
Course
Code
Approved Proposal
Presentation of Proposal
Dissertation
Presentation of Research Findings
at Conferences
Credits
24
24
144
48
Total Credits
1.9.2.5.4.6.2
240
Available Topics/areas of research
Some of the typical areas of current research in the department include Algebra, Functional
Analysis, Linear Operators, Nonlinear Functional Analysis, topology and Differential Equations.
1.9.2.5.4.6.3
Award of Qualification
The minimum number of credits for an MSc is 240, which may be accumulated entirely from a
dissertation or split between coursework and a dissertation.
1.9.2.5.4.6.4
Programme Tuition Fees
Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition
fees, application fees, registration fees, late registration-fees and other student fees.
1.9.2.5.4.6.5 Articulation
Vertical
Vertical Articulation is possible with: PhD Mathematics, NQF Level 10
Horizontal
Within WSU
Horizontal Articulation is possible with NQF Level 9 qualifications offered by WSU.
Other Universities
Horizontal Articulation is possible with NQF Level 9 qualifications offered by other
institutions, subject to the relevant institution’s admission requirements.
1.9.2.5.4.6.6 Service Modules offered by the Department
Site: NMD
Module Name
Code
Credits
Level
Semester
Faculty/Dept
Special Mathematics I
SPM1101
16
I
I
FBML
Special Mathematics I
SPM1201
16
I
II
FBML
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
46
Site: BC
Module Name
Code
Credits
Level
Semester
(Semesters)
Faculty/Dept
Mathematics S2
MATH2/0
10
2
S2
Civil
Quantitative
Techniques
QAT1A13
24
2
S2
Markt
Quantitative
Techniques
QAT1A13
24
2
S2
Markt
Business Calculations
BUC1001
12
1
S1
NHC Acc
Mathematics S1 Ext
EMAT1/0
12
1
S1
Elec
Maths Lit
MATHS10
6
1
S1
Food & C
Mathematics S2
MATH2/0
12
2
S2
Elec
Business Calculations
Group 1
BUC1001
12
1
S1
Acc
Mathematics S1 Ext
MAT11E0
12
1
S1
AC
Mathematics S2
MAT2113
12
2
S2
AC
Mathematics S1
MAT1113
12
1
S1
AC
Mathematics S1
MATH1/0
12
1
S1
Elec
Mathematics S3
MATH3/0
12
3
S3
Elec
Business Calculations
Group 2
BUC1001
12
1
S1
B
Business Calculations
Group 3
BUC1001
12
1
S1
C
Business Calculations
Group 4
BUC1001
12
1
S1
Ext
Mathematics S1
MATH1/0
10
1
S1
Civil
Mathematics S1 Ext
EMAT1/0
10
1
S1
Civil
Mathematics S2 Ext
EMAT2/0
10
2
S2
Civil
Mathematics S4
MATH4/0
12
4
S4
Elec
Quantitative
Techniques Group 1
QAT1B14
10
2
S2
Markt
Quantitative
Techniques Group 2
QAT1B14
10
2
S2
Markt
Statistics Group 1
STA2002
12
2
S2
Acc
Statistics Group 2
BST2002
12
2
S2
Acc
Maths Lit
MATHS20
6
2
S2
F&C
47
2014
PROSPECTUS
Site: Ibika & Chisielhurst
Module Name
Code
Credits
Level
Semester
(Semesters)
Faculty/Dept
Mathematics S1
MATH1/0
10
1
S1
Civil
Mathematics S2
MATH2/0
10
2
S2
Civil
Mathematics S1 Ext
EATH1/0
10
1
S1&S2
Civil
Mathematics S2 Ext
EAHT2/0
10
2
S1 &S2
Civil
Mathematics S1 Ext
EMAT1/0
12
1
S1& S2
Elec
Mathematics S1
MATH1/0
12
1
S1
Elec
Mathematics S2
MATH2/0
12
2
S2
Elec
Mathematics S3
MATH3/0
12
3
S3
Elec
Mathematics S1 Ext
EMAT0/0
12
1
S1&S2
Mech
Mathematics S2 Ext
EMAT2/0
10
2
S1&S2
Mech
Mathematics S1
MATH1/0
12
1
S1
Mech
Mathematics S2
MATH2/0
10
2
S2
Mech
3
S3
Mathematics S3
MATH3/0
10
Applied Statisics
APST2/0
30
IT
IT Electronics
ITEL2/0
15
IT
1.9.3
1.9.3.1
Mech
Department of Statistics
Information about Department
The Department of Statistics is located on the Mthatha campus of the university, at the Nelson
Mandela Drive site offers undergraduate and postgraduate degree programmes in statistics.
In addition it also offers service courses to other departments and faculties. The details of the
programmes are given below
Department Programmes offered
Duration
Full-time
Department
of Statistics
4yrs
Duration Delivery
PartSites
time
N/A
NMD
3yrs
1yrs
2yrs
N/A
3yrs
4yrs
1.9.3.2
BSc Applied Statistical Science Science
- ECP
BSc Applied Statistical Science
BSc Honors Applied Statistical Science
MSc
NMD
NMD
NMD
Mission of the Department
The Department of Statistics strives to serve as a national key source of graduates well-trained
in statistical techniques appropriate for social research in all its dimensions and to provide
training programmes suitable for the skills needs of the computing knowledge industries.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
48
1.9.3.3 Goals of the Department
There are four key components of the goals of the department:
• To produce problem-solving professional statisticians in areas identified in the mission
statement;
• To foster the teaching of statistical methods across the diverse programmes of the Walter
Sisulu University through service courses;
• To promote statistical research in areas relating to national socio-economic development ;
• To contribute significantly to the aims of South African Statistical Association (SASA)
1.9.3.4
Student Societies in the Department
Science Students Societies
1.9.3.5
Programmes In The Department
1.9.3.5.1
BSc Applied Statistical Science
1.9.3.5.1.1
Entrepeneurship & Professional Development of Students
Statistics is an important area of study and is needed in various sectors of government and
industry and commerce. In view of this, the long term plan of the department envisages the
establishment of a linkage between the department and industry and commerce.
1.9.3.5.1.2
Career Opportunities
A Bachelor of Science degree in Applied Statistical Science will prepare the student for jobs
in many different sectors of the economy, including Agriculture, Banking, Economic Planning,
Education, Engineering, Forestry, Health Research, Insurance, Manufacturing, Market Research,
Monitoring & Evaluation, Scientific Research, Social Research, Transport.
1.9.3.5.1.3
Purpose of Qualification
To provide basic statistical knowledge in applied mathematics, computer science, mathematics
and statistics with an inclination towards application in the solution of technical problems in the
marketplace, and for further training at a higher level in various specializations needing a sound
foundation in statistical Sciences.
1.9.3.5.1.4
Exit Level Outcomes of the Programme
A BSc Applied Statistics graduate should:
• demonstrate knowledge and understanding of basic concepts and principles in applied
statistics,
• have a sound basis in applied statistics for further training in this area and/or other fields
of study that require a foundation in applied statistics,
• develop a culture of critical and analytical thinking and be able to apply scientific reasoning
to societal issues,
• demonstrate ability to apply statistics,
• be able to manage and organize own learning activities responsibly,
49
2014
PROSPECTUS
•
be able to demonstrate ability to solve real-world problems requiring the application of
techniques in statistics.
1.9.3.5.1.5
Programme Characteristics
1.9.3.5.1.5.1
Academic and Research Orientated Study
The programme is mainly academic and research orientated because academic study is
combined with related practical work aimed at developing more conceptual mathematical than
computational outcomes. The courses in this programme are developed co-operatively using
inputs from internal and external academic sources on a continuous basis.
1.9.3.5.1.5.2
Practical Work
Practical work in tutorials and computer laboratories provides the practical experience and the
development of computing and research skills that will form the basis of future work, academic
and research engagement.
1.9.3.5.1.5.3
Teaching and Learning Methodology
Learning activities include lectures, tutorials, practicals in which in which independent study
are integrated.
1.9.3.5.1.6 Programme Information
The entire programme must consist of credits from core modules in Statistics and related areas
in the school. See also Section 1.5 for the Minimum Admission Requirements and Section 1.7
for Programme Rules.
1.9.3.5.1.6.1
Curriculum
A student must take all the Core modules and Foundational modules at that level. Relevant
electives (for which the student has the required pre-requisites) must then be chosen so that
the student has a minimum of 120 credits at that level. However, no student may register for
more than 128 credits in any given academic year.
1.9.3.5.1.6.1.1 Core and Foundation Modules
Level 1
Module Name
Core
Probability & Distribution Theory I
Probability & Statistical Inference I
Foundation
Computer Literacy
Communication Skills
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
50
Code
Credits
Semester
STA1101
STA1202
16
16
1
2
CLT1101
EDU1001
8
8
1
1
Total core credits
Elective credits required
Total credits
Level 2
Module Name
Probability & Distribution Theory II
Statistical Inference II
Total core credits
Elective credits required
Total credits
Level 3
Module Name
Sampling Theory & Methods
Stochastic Processes & Time Series Forecasting
Linear Model & Multivariable Distribution theory
Total core credits
Elective credits required
Total credits
48
72
120
Code
STA2101
STA2202
Credits
16
16
32
98
120
Semester
First
Second
Code
STA3203
STA3202
STA3101
Credits
16
16
16
48
72
120
Semester
Second
Second
First
Code
Credits
Semester
CHE1101
CSI1101
CSI1102
PHY1101
MAT1101
MAT1201
CHE1201
CSI1201
PHY1202
APM1101
APM1201
16
8
8
16
16
16
16
8
16
16
16
First
First
First
First
First
Second
Second
Second
Second
First
Second
Code
APM2101
MAT2102
MAT2202
APM2201
APM2202
CHE2102
Credits
16
8
8
16
16
16
Semester
First
Second
Second
Second
First
First
1.9.3.5.1.6.1.2 Electives
Level 1
Module Name
General Chemistry I
Information Systems and Applications
Problem Solving and Programming
General Physics I
Precalculus & Calculus I
Precalculus & Calculus II
General Chemistry I
Problem Solving and Programming
General Physics II
Introduction to Linear & Vector Alg.
Linear Programming & Applied Computing
Level 2
Module Name
Numerical Analysis I
Real Analysis I
Linear Algebra I
Eigenvalue Problems and Fourier Analysis
Mechanics I
Analytical Chemistry II
51
2014
PROSPECTUS
Physical Chemistry II
Programming in JAVA
Mechanics & Waves
Multivariable Calculus
Inorganic Chemistry II
Organic Chemistry II
Thermodynamics and Modern Physics
Operating Systems
Ordinary Differential Equations
Minimum total credits
Level 3
Module Name
Numerical Methods
Linear Algebra II
Inorganic Chemistry III
Organic Chemistry III
Introduction to Artificial Intelligence
Software Engineering I
Electromagnetism and Quantum Mechanics
Linear Models & Multivariable Distribution Theory
Analytical Chemistry III
Physical Chemistry III
Environmental Chemistry – 2003
Data Management
Software Engineering II
Statistical Mechanics and Solid State Physics
Complex Analysis
Mathematical Programming
CHE2105
CSI2101
PHY2101
MAT2101
CHE2203
CHE2204
PHY2202
CSI2201
MAT2201
16
14
16
8
16
16
16
14
8
56
First
First
First
First
Second
Second
Second
Second
First
Code
APM3101
MAT3102
HE3103
CHE3104
CSI3101
CSI3102
PHY3101
STA3101
CHE3202
CHE3205
CHE3207
CSI3201
(CSI3202
PHY3202
MAT3202
APM3201
Credits
16
16
16
8
14
14
24
16
16
16
12
14
14
24
16
16
Semester
First
First
First
First
First
First
First
First
Second
Second
Second
Second
Second
Second
Second
Second
1.9.3.5.1.6.1.3 Pre-Requisite Courses
Module
STA1101
Prerequisite
STA1202
STA2101
STA1101
STA1202
MAT1101
MAT1201
APM1101
APM1201
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
Concurrent
MAT1101
APM1101
MAT1201
APM1201
MAT2101
MAT2102
APM2101
52
Substitutes
STA2201
STA3101
STA3202
1.9.3.5.1.6.2
STA1101
STA1202
MAT1101
MAT1201
APM1101
APM1201
STA2101
STA2202
MAT2201
MAT2202
APM2201
MAT3101
MAT3102
APM3101
MAT3201
MAT3202
APM3201
STA2101
STA2202
Award of Qualification
The qualification will be awarded after one satisfies the programme requirements, including
completing 360 credits with a minimum of 120 credits obtained at each level. See also Rule G12
of the General Prospectus.
1.9.3.5.1.6.3
Programme Tuition Fees
Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition
fees, application fees, registration fees, late registration-fees and other student fees.
1.9.3.5.1.6.4
Articulation
Vertical
Vertical Articulation is possible with BSc Hons Mathematics and BSc Hons Applied Mathematics,
NQF Level 8
Horizontal
Within WSU
Horizontal Articulation is possible with NQF Level 7 qualifications offered by WSU, e.g. BSc
Applied Mathematics, NQF Level 7, course to the admission requirements of that qualification.
Other Universities
Horizontal Articulation is possible with NQF Level 7 qualifications offered by such institutions,
subject to the relevant institution’s admission requirements.
1.9.3.5.1.6.5
Core Syllabi of Courses offered
NB. Course information on some of the modules offered outside the departments of statistics
may be obtained from the respective departments.
STA 1101: Probability & Distribution Theory 1
Module Code
Module Name NQF Level
Credits
Semester
STA1101
5
16
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
4 x 50 min
1 x 100 min
13
160
53
2014
PROSPECTUS
Content / Syllabus Data analysis and Descriptive Statistics
Different kinds of variables and measurement scales. Construction and
Graphical presentation of frequency distributions. Cumulative frequency;
the ogive and percentiles. Measures of central tendency; the Mean,
Median and Mode. Measures of Spread; Mean Deviation, the Standard
Deviation and the Quartile Deviation.
Probability Distributions
Introduction to the concept of probability. Counting techniques, Baye’s
theorem. Discrete probability distributions, including the Bernoulli, the
Binomial, Poisson, Hyper-geometric, and Negative Binomial. Continuous
Probability distributions including the Uniform, the Gamma, the Beta and
the Chi-Square distributions, the Normal distribution.
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
STA1202: Statistical Inference I
Module Code
Module Name NQF Level
Credits
Semester
STA1202
5
16
2
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
4 x 50 min
1 x 100 min
13
160
Content / Syllabus Inferential Statistics: The Central Limit Theorem. Introduction to Sampling
distributions including the t-distribution, the Chi-Square distribution and
the F-distribution. Estimation of parameters. One and Two sample tests
of hypotheses for means. The F-test. Simple Correlation, Simple Linear
Regression
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
STA2101: Probability & Distribution Theory II
Module Code
Module Name NQF Level
Credits
Semester
STA2101
6
16
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
4 x 50 min
1 x 100 min
13
160
Content / Syllabus Combinatorial analysis, axioms of probability, conditional probability
and stochastic inde­pendence. Introduction to the concept of a random
variable. More detailed treatment of discrete probability distribution,
Introduction to mathematical expectation and moment generating
functions, Jointly distributed random variables, independent random
variables, marginal and conditional distributions. The bivariate normal
distribution, Functions of random variables; sums of random variables,
The central limit theorem. Chebychev‘s inequality, De-Moivre-Laplace
theorem. Poisson approximation to the binomial distribution.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
54
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x 60%
+ Exam Mark x 40%.
STA2202: Statistical Inference II
Module Code
Module Name NQF Level
Credits
Semester
STA2202
6
16
2
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
4 x 50 min
1x 100 min
13
160
Content / Syllabus Estimation: Properties of good estimators. Unbiased estimators.
Consistent estimators. Maximum like¬lihood, method of moments, and
least squares estimators. Interval estimation; confidence intervals for
means, difference between two means, proportions. Confidence intervals
for variances and ratio of variances.
Assessment
Hypothesis testing: Testing a statistical hypothesis; the Neyman-Pearson
Lemma, the power function of a statistical test. likelihood ratio tests.
Applications of hypothesis testing; tests concerning means, difference
between two means, variances, proportions, differences among k
proportions.
Analysis of contingency tables, correlation and regression analysis,
including multiple linear regression and correlation. Introduction to time
series forecasting
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
STA3101: Multivariable Distribution Theory & Linear Models
Module Code
Module Name NQF Level
Credits
Semester
STA3101
7
16
2
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
4 x 50 min
1x 100 min
13
160
Content / Syllabus Multivariate Distribution Theory: Random Vector: p-dimensional case ,
Joint distribution and their applications: p-dimensional case; Marginal &
Conditional distributions and their applications to probability calculations,
Marginal and Product Moments; Mean Vector; Covariance Matrix;
Dispersion Matrix; Expectation of Random Quadratic Form. Joint Moment
Generating Function and its applications; The Multivariate Normal
Distribution; Quadratic Forms in Normal Variates.
Linear Models: Concepts related to linear models; point and interval
estimation; hypothesis testing; violation of assumptions; applications of
linear models.
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
55
2014
PROSPECTUS
STA3202: Time Series & Stochastic Processes
Module Code
Module Name NQF Level
Credits
Semester
STA3202
7
16
2
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
4 x 50 min
1x 100 min
13
160
Content / Syllabus Stochastic Processes: Introduction to stochastic processes. Finite markov
chains with special emphasis on two state markov chains. Classification
of states. The basic limit theorem of markov chains. Simple markov
processes. The Poisson process. Birth and death processes. Introduction
to inference for markov chains and markov processes.
Time series forecasting: Forecasting a time series with no trend,
forecasting a time series with a linear trend, fore­casting a time series with
a quadratic trend. Forecasting seasonal time series. The multipli­cative
decomposition model, Winter’s method. Forecasting a time series with
additive sea­sonal variation; the use of regression models. Application of
forecasting techniques.
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
1.9.3.5.2
BSc Applied Statistical Science (Extended Programme)
The first 2 years of the BSc Statistical Science (Extended Programme) are equivalent to the
first year of the BSc Statistical Science programme. In the last two years of the BSc Statistical
Science (Extended Programme) the students follow the BSc Statistical Science programme from
second year. See section 1.5.2.5.1
At each of the years, 1, 2, 3 & 4, a student must accumulate at least 120 credits towards the
total graduation credits. All the core modules (and foundation modules in the case of Level 1)
must be taken at each Level. The remaining credits to satisfy the credit requirements at the
respective level must be accumulated from the electives. The following table captures briefly
the admission requirement and programme characteristics.
See also Section 1.6 for Admission Requirements and Programme and Characteristics.
1.9.3.5.2.1
1.9.3.5.2.1.1
Curriculum
Core and Foundation Modules
Level 1a (BSCEAS)
Module Name
Core
Integrated Statistics I
Integrated Statistics II
Integrated Mathematics I
Integrated Mathematics II
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
56
Code
Credits
Semester
STA1111
STA1212
MAT1111
MAT1212
16
16
16
16
First
Second
First
Second
Foundation
Computer Science Fundamentals
Academic Literacy I
Life Skills I
Introduction to Programming I
Academic Literacy II
Life Skills II
Level 1b (BSCEAS)
Module Name
Core
Integrated Statistics III
Integrated Statistics IV
Integrated Mathematics III
Integrated Mathematics IV
Foundation
Introduction to Computer Architecture
Introduction to Programming II
1.9.3.5.2.1.2
CSI1111
ACL1111
LSK1111
CSI1212
ACL1212
LSK1212
16
8
8
16
8
8
First
First
First
Second
Second
Second
Code
Credits
Semester
STA1113
STA1214
MAT1113
MAT1214
16
16
16
16
First
Second
First
Second
CSI1113
CSI1214
16
16
First
Second
Electives
Level 1a (BSCEAS) – An elective cannot be taken, presently, at this year because
of exceeding credits
Module Name
Code
Credits
Semester
Extended General Physics I
PHY1111
16
First
Extended General Chemistry I
CHE1111
16
First
Extended General Physics II
PHY1212
16
Second
Extended Organic and Physical Chemistry I
CHE1212
16
Second
Level 1b (BSCEAS)
Module Name
Code
Credits
Semester
Introduction to Linear & Vector Algebra
APM1101
16
First
Extended General Physics III
PHY1113
16
First
Extended General Chemistry II
CHE1113
16
First
Probability & Distribution theory I
STA1101
16
First
Linear Programming & Applied Computing
APM1201
16
Second
Extended General Physics IV
PHY1214
16
Second
Extended Organic and Physical Chemistry II
CHE1214
16
Second
Statistical Inference I
STA1202
16
Second
1.9.3.5.2.1.3
Pre-Requisite Courses
Course Code
STA1111
STA1212
Course Name
Integrated Statistics I
Integrated Statistics II
Pre-Requisite
Faculty admission requirements
Faculty admission requirements
57
2014
PROSPECTUS
STA1113
STA1214
MAT1111
MAT1212
MAT1113
MAT1214
1.9.3.5.2.2
Integrated
Integrated
Integrated
Integrated
Integrated
Integrated
Statistics III
Statistics IV
Mathematics
Mathematics
Mathematics
Mathematics
I
II
III
IV
Faculty admission requirements
FACULTY admission requirements
MAT1111
MAT1212
Award of Qualification
The qualification will be awarded after satisfaction of the programme requirements, including
completing 360 credits with a minimum of 120 credits obtained at each level. Also see Rule G12
of the General Prospectus.
1.9.3.5.2.3
Programme Tuition Fees
Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition
fees, application fees, registration fees, late registration-fees and other student fees.
1.9.3.5.2.4
Articulation
Vertical
Vertical Articulation is possible with BSc Hons Mathematics and BSc Hons Applied Mathematics,
NQF Level 8
Horizontal
Within WSU
Horizontal Articulation is possible with NQF Level 7 qualifications offered by WSU, e.g. BSc
Applied Mathematics, NQF Level 7, course to the admission requirements of that qualification.
Other Universities
Horizontal Articulation is possible with NQF Level 7 qualifications offered by such institutions,
subject to the relevant institution’s admission requirements.
1.9.3.5.2.5
Core Syllabi of Courses Offered
STA1111: Integrated Statistics I
Module Code
Module Name NQF Level
Credits
Semester
STA1111
5
16
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 100 min
13
160
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
58
Content / Syllabus Descriptive Statistics: Different kinds of variables and measurement scales;
Tabular and graphic presentation of data. Construction of frequency
tables and their graphic presentation; Relationship of histogram with
frequency curve; Stem & leaf diagram; Commonly used fractiles: their
meanings and properties, Descriptive measures of central tendency and
their properties; Descriptive measures of variation/dispersion and their
properties. Economic Statistics (Index Numbers): Characteristics of index
numbers of prices; Types of index numbers of prices & Methods of their
construction: simple aggregative , weighted aggregative; quantity index
numbers; cost of living index numbers.
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
STA1212: Integrated Statistics II
Module Code
Module
Name
NQF Level
Credits
Semester
STA1212
5
16
2
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 100 min
13
160
Content / Syllabus Point & Interval Estimation : Meaning of point estimate . Illustrations
with commonly used point estimates for population mean , variance ,and
proportion . Basic normal-theory interval estimation of these parameters
(both one-sample & two-sample cases). Hypothesis Testing : Normaltheory one-and two-sample-based tests of hypotheses about population
means , variances & proportions. The chi-square test for independence .
Simple Regression : Elementary treatment of the simple linear model.
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
STA1113: Integrated Statistics III
Module Code
Module
Name
NQF Level
Credits
Semester
STA1113
5
16
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 100 min
13
160
Content / Syllabus Set Theory: Definition and examples of a set; Common set operations
using Venn diagram; Basic laws of set algebra. Counting Techniques:
Product rule for counting; concept of permutation and associated rules;
concept of combination and associated rules. Probability I: Definition of
probability. Basic rules for probability. Distributions I: Discrete probability
distributions in general . The simple treatment of properties and probably
calculations involving discrete uniform distribution , the Bernoulli,
binomial, negative binomial Hypergeometric & Poisson distributions.
Continuous distributions in general . The simple treatment of properties
and probability calculations involving continuous uniform distribution ,
the nor­mal and the associated sampling distributions .
59
2014
PROSPECTUS
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
STA1214: Integrated Statistics IV
Module Code
Module Name
STA1214
Lectures per week Pracs per week
2 x 50 min
NQF Level
Credits
Semester
5
16
2
Tutorials per week Number of weeks Notional hours
1 x 100 min
13
160
Content / Syllabus Point & Interval Estimation of parameters in general. One - and - two
sample tests of hypotheses about population means, variances , &
proportions. Correlation and regression. Significance tests in correlation.
Linear regression point prediction. Curvillinear regression, significance
tests in simple linear regression. Introduction to non-parametric tests.
The sign test, Wilcoxon’s paired-sample test, Mann­Whitney U-test
Assessment
Semester Mark (DP) will be obtained assessments based on assignments
and tests. Final mark will be obtained from the Semester Mark (DP) x
60% + Exam Mark x 40%.
1.9.2.5.3 BSc Honours (Statistical Science)
1.9.3.5.3.1 Entrepreneurship & Professional Development of Students
Statistics is a scarce skill in South Africa and is crucial to the scientific and technological
development that leads to economic development of the country. In view of this, the long term
plan of the department envisages the establishment of a linkage between the department and
industry and commerce.
1.9.3.5.3.2
Career Opportunities
A Bachelor of Science degree in Applied Statistical Science will prepare the student for jobs
in many different sectors of the economy, including Agriculture, Banking, Economic Planning,
Education, Engineering, Forestry, Health Research, Insurance, Manufacturing, Market Research,
Monitoring & Evaluation, Scientific Research, Social Research, Transport.
1.9.3.5.3.3
Purpose of Qualification
To provide advanced knowledge in Applied Statistical Sciences and prepare students for
placement in various types of sectors. See also Section 1.9.3.5.1.3 for BSc Applied Statistical
Science.
1.9.3.5.3.4
Exit Level Outcomes of the Programme
After the successful completion of the programme the student will be able to utilize the acquired
skills in various disciplines such as Science and Engineering, Economic Sciences, Social Sciences
and Humanities.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
60
1.9.3.5.3.5
Programme Characteristics
1.9.3.5.3.5.1
Academic and Research Orientated
The programme is mainly academic and research orientated because academic study is research
based and aimed at developing conceptual statistical outcomes and training in new knowledge
generation.
1.9.3.5.3.5.2
Practical Work
Research work provides the practical experience and the development of computing and
research skills that will form the basis of future work, academic and research engagement.
1.9.3.5.3.5.3
Teaching and Learning Methodology
Learning activities include lectures, assignments, proposal development, hypothesising research
problems, data collection, capturing, analysis, interpretation, report writing, communications
such as conference posters, papers. The programme is accredited with CHE and HEQC.
1.9.3.5.3.6 Programme Information
The entire programme is designed to consist of courses/modules in advanced Statistics.
1.9.3.5.3.6.1
Minimum Admission Requirements
An overall minimum of 55% in BSc in Statistics or an equivalent area. See also Section 1.8 for
Programme Rules.
1.9.3.5.3.6.2
Selection Criteria for New Students
All applicants will be interviewed for selection into the programme and immediately allocated
supervisors for the research component of the course.
1.9.3.5.3.6.3
Curriculum
1.9.3.5.3.6.3.1 Core and Foundation Modules
Level 1
Module Name
Elective 1
Elective 2
Elective 3
Elective 4
Elective 5
Total credits
Code
Code
Code
Code
Code
Code
61
Credits
24
24
24
24
24
120
Semester
1 and/or 2
1 and/or 2
1 and/or 2
1 and/or 2
1 and/or 2
2014
PROSPECTUS
1.9.3.5.3.6.3.2 Electives
Level 1
Module Name
Advanced Probability and distribution theory
Advanced Parametric statistical inference
Advanced sampling theory & methods
Advanced design and analysis of experiments
Advanced general linear model
Advanced Analysis of contingency tables
Advanced nonparametric statistical inference
Advanced Multivariate distribution theory
Advanced special topics: Time series analysis
Honours project (compulsory)
Code
STA 4001
STA4002
STA4003
STA4004
STA4005
STA4006
STA4007
STA4008
STA4009
STA4010
Credits
24
24
24
24
24
24
24
24
24
8
1.9.3.5.3.6.3.3 Pre-Requisite Courses & Available Electives
See Section 1.9.3.5.3.6.3.1 and 1.9.3.5.3.6.3.2— Curriculum
1.9.3.5.3.6.4
Award of Qualification
The qualification will be awarded after one completes 120 credits. Also see Rule G12 of the
General Prospectus.
1.9.3.5.3.6.6
Programme Tuition Fees
Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition
fees, application fees, registration fees, late registration-fees and other student fees.
1.9.3.5.3.6.6 Articulation
Vertical
Vertical Articulation is possible with MSc Statistics, NQF Level 9
Horizontal
Within WSU
Horizontal Articulation may be possible with some NQF Level 8 qualifications offered by WSU.
Other Universities
Horizontal Articulation is possible with NQF Level 8 qualifications offered by other institutions,
subject to the relevant institution’s admission requirements.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
62
1.9.3.5.3.6.7
Core Syllabi of Courses Offered
STA4001: Advanced Probability and distribution theory
Module Code
Module Name NQF Level
Credits
Semester
STA4001
8
24
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
Content / Syllabus Probability axioms, probability of finite sample spaces, conditional
probability, and Bayes’ theorem. Random variables; Transformation of
random variables; Order statistics. Mo­
ments and moment generating
functions, Special distributions, Modes of convergence; con­vergence in
probability, almost sure convergence, The weak and the strong laws of
large numbers, The central limit theorem, Sampling distributions.
Assessment
Year Mark (DP) will be obtained from assessments based on assignments
and tests. Final mark will be obtained from the Year Mark (DP) x 60% +
Exam Mark x 40%.
STA4002: Advanced parametric statistical inference
Module Code
Module Name NQF Level
Credits
Semester
STA4002
8
24
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
Content / Syllabus Tests of significance; Point estimation; minimum variance unbiased
estimation least square estimation, maximum likelihood estimation,
Interval estimation, Hypothesis testing; Neyman-Pearson theory.
Generalised likelihood ratio test, Asymptotic theory, Bayesian methods.
Assessment
Year Mark (DP) will be obtained from assessments based on assignments
and tests. Final mark will be obtained from the Year Mark (DP) x 60% +
Exam Mark x 40%.
STA4003: Advanced sampling theory and methods
Module Code
Module Name NQF Level
Credits
STA4003
8
24
Lectures per week Pracs per week Tutorials per week Number of weeks
2 x 50 min
1 x 50 min
13
Semester
1
Notional hours
Content / Syllabus Advanced treatment of the commonly used sampling procedures,
Multi-stage and multi­phase sampling; Non-sampling errors, Sequential
sampling; Sequential probability ratio test, Sampling inspection and
quality control.
Assessment
Year Mark (DP) will be obtained from assessments based on assignments
and tests. Final mark will be obtained from the Year Mark (DP) x 60% +
Exam Mark x 40%.
63
2014
PROSPECTUS
STA4004: Advanced design and analysis of experiments
Module Code
Module Name NQF Level
Credits
Semester
STA4004
8
24
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
Content / Syllabus Confounding in factorial experiments, Fractional replication, Response
surface designs, Incomplete block designs.
Assessment
Year Mark (DP) will be obtained from assessments based on assignments
and tests. Final mark will be obtained from the Year Mark (DP) x 60% +
Exam Mark x 40%.
STA4005: Advanced general linear model
Module Code
Module Name NQF Level
Credits
Semester
STA4005
8
24
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
Content / Syllabus Applications of the general linear model, The regression model,
Applications of the regres­sion and design models, The components -ofvariance model. ­
Assessment
Year Mark (DP) will be obtained from assessments based on assignments
and tests. Final mark will be obtained from the Year Mark (DP) x 60% +
Exam Mark x 40%.
STA4006: Advanced Analysis of contingency tables
Module Code
Module Name NQF Level
Credits
STA4006
8
24
Lectures per week Pracs per week Tutorials per week Number of weeks
2 x 50 min
1 x 50 min
13
Semester
1
Notional hours
Content / Syllabus Contingency tables and the chi-square test, 2x2 tables, McNemar’s test,
Combining infor­
mation from several tables, Measures of association
for contingency tables; Multi-dimen­sional tables, Log-linear models for
contingency tables.
Assessment
Year Mark (DP) will be obtained from assessments based on assignments
and tests. Final mark will be obtained from the Year Mark (DP) x 60% +
Exam Mark x 40%.
STA4007: Advanced nonparametric statistical inference
Module Code
Module Name NQF Level
Credits
Semester
STA4007
8
24
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
64
Content / Syllabus Introduction to order statistics; Goodness-of-fit tests; the chi-square
test, the Kolmogorov ­Smirnov one sample test. The sign test, the signedrank test; Two-sample problem; Mann-Whitney U-test; Linear rank test
statistics for the location and scale parameters.
Assessment
Year Mark (DP) will be obtained from assessments based on assignments
and tests. Final mark will be obtained from the Year Mark (DP) x 60% +
Exam Mark x 40%.
STA4008: Advanced Multivariate distribution theory
Module Code
Module Name NQF Level
Credits
Semester
STA4008
8
24
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
Content / Syllabus The multivariate normal distribution, The Wishart distribution, Hypothesis
testing concern­ing mean vectors, Application of Hotelling’s T2 –statistics,
Multivariate analysis of variance. Introduction to principal components,
factors analysis, and discriminant analysis.
Assessment
Year Mark (DP) will be obtained from assessments based on assignments
and tests. Final mark will be obtained from the Year Mark (DP) x 60% +
Exam Mark x 40%.
STA4009: Advanced special topics: Time series analysis
Module Code
Module Name NQF Level
Credits
Semester
STA4009
8
24
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
Content / Syllabus Estimation in the domain; Estimating the autocovariance and the
autocorrelation functions, Interpreting the correlogram Fourier
transformation; Deterministic Sinusoidal perturbation, Fourier analysis,
Simple Sinusoidal model, The Nyquist frequency, Periodogram analysis,
Transforming the truncated autocovariance function, Hanning and
Hamming techniques, Smoothing the periodogram, Fourier transform.
Confidence intervals for the spectrum, A comparison of different
estimation procedures, Analyzing a continuous time series, Bivariate
processes, Cross-covariance and Cross-correlation function,
State-space models and the Kalmanfilter; Steady models, linear growth
models, Forecasting; Univariate and Multivariate forecasting procedures,
Modeling seasonality using dummy variable regression.
Assessment
Year Mark (DP) will be obtained from assessments based on assignments
and tests. Final mark will be obtained from the Year Mark (DP) x 60% +
Exam Mark x 40%.
65
2014
PROSPECTUS
STA4010: Honours project (compulsory)
Module Code
Module Name NQF Level
Credits
Semester
STA4010
8
32
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
2 x 50 min
1 x 50 min
13
Content / Syllabus The topic for the Honours project must be chosen from one of the nine
module topics listed above.
The findings from the project must be submitted in a short dissertation
which will be examined by its supervisor and at least one external
assessor.
Assessment
1.9.3.5.4
Year mark (DP) will be obtained from assessments based on assignments
and tests. Final mark will be obtained from the Year Mark (DP) x 60% +
Exam Mark x 40%.
MSc (Applied Statistical Science)
Candidates will be examined either on two (2) papers set on approved subjects and a
dissertation, or on a dissertation only.
1.9.3.5.4.1
Entrepreneurship & Professional Development of Students
Statistical Science is a scarce skill in South Africa and is crucial to the scientific and technological
development that leads to economic development of the country. In view of this, the long term
plan of the department envisages the establishment of a linkage between the department and
industry and commerce.
1.9.3.5.4.2
Career Opportunities
A Master of Science degree in Statistical Science will prepare the student for jobs in statistics,
actuarial sciences, mathematical modeling, and cryptography; for teaching; as well as
postgraduate training leading to a research career in Statistical Science. A strong background
in Statistical Science is also necessary for research in many areas of computer science, social
science, and engineering
1.9.3.5.4.3
Purpose of Qualification
To provide Statistical Science knowledge needed for placement in jobs requiring a significant
amount of statistical maturity, and for further training at a higher level in various specializations
of Statistical Science.
1.9.3.5.4.4
Exit Level Outcomes of the Programme
After the successful completion of the programme the student will be able to utilize the acquired
skills in various disciplines such as Science and Engineering, Economic Sciences, Social Sciences
and Humanities.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
66
1.9.3.5.4.5
Programme Characteristics
1.9.3.5.4.5.1
Academic and Research Orientated
The programme is mainly academic and research orientated because academic study is
research based and aimed at developing conceptual mathematical outcomes and training in
new knowledge generation.
1.9.3.5.4.5.2
Practical Work
Research work provides the practical experience and the development of computing and
research skills that will form the basis of future work, academic and research engagement.
1.9.3.5.4.5.3
Teaching and Learning Methodology
Learning activities include proposal development, hypothesising research problems, data
collection, capturing, analysis, interpretation, report writing, communications such as conference
posters, papers. The programme is accredited with CHE and HEQC.
1.9.3.5.4.6
Programme Information
1.9.3.5.4.6.1
Minimum Admission Requirements
A BSc Honours degree in Statistical Science.
1.9.3.5.4.6.2
Selection Criteria for New Students
All applicants will be interviewed for selection into the programme and immediately allocated
supervisors.
1.9.3.5.4.6.1
Curriculum
Core and Foundation Modules
Year Level
1
1
2
2
Semester
1
2
3
4
Course
Approved Proposal
Presentation of Proposal
Dissertation
Presentation of Research Findings at
Conferences
Total Credits
1.9.3.5.4.6.2
Code
CHE5108
CHE5208
CHE5308
CHE5408
Credits
24
24
144
48
240
Available Topics/areas of research
Typical areas of current research in the department include Tensor methods in statistics and
Non-linear regression analysis of data.
67
2014
PROSPECTUS
1.9.3.5.4.6.3
Award of Qualification
The minimum number of credits for an MSc is 240, which may be accumulated entirely from a
dissertation or split between coursework and a dissertation.
1.9.3.5.4.6.4
Programme Tuition Fees
Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition
fees, application fees, registration fees, late registration-fees and other student fees.
1.9.3.5.4.6.5
Articulation
Vertical
Vertical Articulation is possible with: PhD Mathematics, NQF Level 10
Horizontal
Within WSU
Horizontal Articulation is possible with NQF Level 9 qualifications offered by WSU.
Other Universities
Horizontal Articulation is possible with NQF Level 9 qualifications offered by other institutions,
subject to the relevant institution’s admission requirements.
1.9.3.5.4.6.6 Service Modules offered by the Department
Site: NMD
Module Name
Code
Credits
Level Semester Faculty/Dept
Applied Statistics I
APS1101
16
I
1
FBML, FSET, EDUCATION
Applied Statistics II APS1201 16
I
2
Course descriptors - Electives from other schools
FBML, FSET, EDUCATION
General Chemistry (Analytical and Inorganic)
Module Code
CHE 1101
Contact hours
Module Name
Lectures/Tutorials per week
5 (4 lectures + 1 tutorial)
NQF Level
7
Practicals
per week
1(3 hours)
Credits
Semester
16
1
Number of N o t i o n a l
weeks
hours
12
160
Content / Syllabus Theory: 1. Matter and measurements; Mole concept and stoichiometry;
Reactions between ions in aqueous solutions; Atoms, Molecules and Ions;
Atomic theory, Periodic properties of the elements; Basic concepts of
chemical bonding, Shapes of molecules
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
68
Module Outcomes After engagement with the module content and processes, the students
should be able to: articulate basic chemistry terms/concepts, perform
calculations based on chemical relationships, comprehend and follow
experimental procedure, carry out experiments in chemistry, interpret
experimental results, define different chemical methods, be aware of
safety procedures in handling hazardous materials.
Learning and Teaching Session Number Hours
Total
Learning
and
Lectures & Tutorials (4L + 1T)
12
5
60
Teaching
Practicals
12
3
36
breakdown
Total
96
Assessment
Assessment Sessions
Number Hours
Total
breakdown
Tests
2
2
4
Assignments
2
Practical reports
12
Examination
1
3
3
Supp-examination
1
3
3
Total
7
Projected
self Self study Sessions
Number Hours
Total
study
time Private study
57
breakdown
Grand Total
160
C o n t i n u o u s Assignments: 15% Tests: 60% Practical mark: 25%
Assessment (CA) Continuous assessment (CA) : Overall assessment (OA) = 60 : 40.
Examination
Written examination (WA) : overall assessment (OA) = 40 : 60.
General Chemistry (Physical and Organic)
Module Code
Module Name
CHE 1201
Contact hours
Lectures/Tutorials per week
5 (4 lectures + 1 tutorial)
Content / Syllabus
Module Outcomes
N Q F
Level
7
Practicals
per week
1(3 hours)
Credits
16
Number
weeks
12
Semester
1
of N o t i o n a l
hours
160
Theory: First year organic chemistry course = 24 lectures. 1. Introduction
: Scope of organic chemistry. 2. General Principles. 3. Hydrocarbons.
4. Organic halogen compounds 5. Alcohols. 6. Aldehydes and ketones.
7. Carboxylic acids and their derivatives. 8. Amines.
First Year Physical Chemistry Course = 24 lectures. 1. Intermolecular
Forces, Liquids & Solids 2. Chemical thermodynamics. 3. Chemical
equilibrium. 4. Acid and base equilibria. 5. Electrochemistry. 6.
Introduction to chemical kinetics.
After engagement with the module content and processes, the students
should be able to: articulate basic chemistry terms/concepts, perform
calculations based on chemical relationships, comprehend and follow
experimental procedure, carry out experiments in chemistry, interpret
experimental results, define different chemical methods, be aware of
safety procedures in handling hazardous materials
69
2014
PROSPECTUS
Learning
and
Teaching
breakdown
Assessment
breakdown
Projected self study
time breakdown
Continuous
Assessment (CA)
Examination
Learning and Teaching Session Number
Hours
Total
Lectures & Tutorials (4L + 1T)
12
5
60
Practicals
12
3
36
Total
96
Assessment Sessions
Number
Hours
Total
Tests
2
2
4
Assignments
2
Practical reports
12
Examination
1
3
3
Supp-examination
1
3
3
Total
7
Self study Sessions
Number
Hours
Total
Private
study
(include
57
assignments and self study)
Grand Total
160
Assignments: 15% Tests: 60% Practical mark: 25%
Continuous assessment (CA) : Overall assessment (OA) = 60 : 40.
Written examination (WA) : overall assessment (OA) = 40 : 60.
Analytical Chemistry II
Module Code
CHE 2102
Contact hours
Content /
Syllabus
Module Name
NQF Level
Credits
Semester
7
16
1
Lectures/Tutorials Practicals per week Number of weeks N o t i o n a l
per week
hours
4 hours (at least 1 6 hours
12
160
hour tutorial)
Tools of Analytical Chemistry: Introduction to Analytical Chemistry.
Calculations used in Analytical Chemistry. Errors in Chemical Analysis.
Random Errors in Chemical Analysis. Statistical Data Treatment and
Evaluation. Sampling, Standardization and Calibration. Quality Assurance in
Chemical Analysis
Chemical Equilibria: Aqueous Solutions and Chemical Equilibria. Effects
of Electrolytes on Chemical Equilibria. Solving Equilibrium Calculations for
Complex Systems. Classical Methods of Analysis. Gravimetric Methods of
Analysis. Titrimetric Methods of Analysis: Precipitation Titrimetry. Principles
of Neutralization Titrations. Titration Curves for Complex Acid/ Base
Systems. Applications of Neutralization Titrations. Complexation Reactions
and Titrations. Electrochemical Methods of Analysis. Introduction to
Electrochemistry. Applications of Standard Electrode Potentials. Applications
of Oxidation / Reduction Titrations. Potentiometry
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
70
Module
Outcomes
Learning
and
Teaching
breakdown
Assessment
breakdown
Projected self
study time
breakdown
Continuous
Assessment
(CA)
Examination
After engagement with the module content and processes, the students
should be able to: Draw a representative sample and prepare it for
chemical analysis; apply appropriate statistical techniques to obtain useful
chemical information from raw data; operate a chemical quality assurance
programme; have a knowledge of sampling and the principles of gravimetry
and titrimetry; demonstrate competence in the practical use of gravimetric
and titrimetric techniques in carrying out analysis; have ability to perform
the calculations required to obtain useful chemical information from given
analytical data.
Learning and Teaching Session
Number
Hours
Total
Lectures & Tutorials
12
4
48
*Practicals
6
6
36
Total
84
Assessment Sessions
Number
Hours
Total
Tests (All levels)
2
2
4
Assignments
2
Practical reports
6
Examination
1
3
3
Supp-examination
1
3
3
Grand Total
7
Self study Sessions
Number
Hours
Total
Private study
69*
Grand Total
160
Assignments: 15% Tests: 60% Practical mark: 25%
Continuous assessment (CA) : Overall assessment (OA) = 60 : 40.
Written examination (WA) : overall assessment (OA) = 40 : 60.
Analytical Chemistry III
Module Code
CHE 3202
Contact hours
Module Name
Analytical Chemistry III
Lectures/Tutorials per week
NQF Level
7
Pracs per
week
4 hours (at least 1 hour tutorial) 6 hours
Content / Syllabus
Credits
16
Number
of
weeks
12
Semester
1
Notional
hours
160
Electrochemical Methods of analysis. Coulometry. Voltammetry.
Spectral Methods of Analysis. Introduction to spectrophotometry.
Molecular spectroscopy, Molecular spectroscopy equipment, Atomic
spectroscopy. Chemical Separation Methods, Solvent extraction,
Chromatography theory, Gas chromatography, Liquid chromatography,
Other Chromatographic Techniques, Supercritical fluid chromatography,
Electrophoresis, Affinity chromatography, Field Flow Fractionation, Mass
Spectrometry for chromatographers, Hyphenated (Ancillary) Methods,
Multidimensional chromatography, Introduction to Thermal Methods of
Analysis, Introduction to Radiochemical Methods of Analysis.
71
2014
PROSPECTUS
Module Outcomes
Learning
and
Teaching
breakdown
Learning and Teaching Session Number
Hours
Total
Lectures & Tutorials
12
4
48
Practicals
12
6
36
Total
84
Assessment
Assessment Sessions
Number
Hours
Total
breakdown
Tests
2
2
4
Assignments
2
Practical reports
6
Examination
1
3
3
Supp-examination
1
3
3
Grand Total
7
Projected self study Self study Sessions
Number
Hours
Total
time breakdown
Private study
59
Grand Total
160
Continuous
Assignments: 15% Tests: 60% Practical mark: 25%
Assessment (CA)
Continuous assessment (CA) : Overall assessment (OA) = 60 : 40.
Examination
Written examination (WA) : overall assessment (OA) = 40 : 60.
Inorganic Chemistry II
Module Code
CHE 2203
Contact hours
Module Name
NQF
Level
Inorganic Chemistry
7
Lectures/Tutorials per week
Pracs per
week
4 hours (at least 1 hour tutorial): 6 hours
Credits
16
Number
weeks
12
Semester
1
of N o t i o n a l
hours
160
Content / Syllabus Theory: 1. The chemical bond. 2. Descriptive chemistry of the P-block
elements.
3.Coordination chemistry. 4. Inorganic rings, chains and cages
Learning
Learning and Teaching Session
Number
Hours
Total
and
Lectures & Tutorials
12
4
48
Teaching
Practicals
12
6
72
breakdown
Total
120
Assessment
Assessment Sessions
Number
Hours
Total
breakdown
Tests (All levels)
2
2
4
Assignments
2
Practical reports
6
Examination
1
3
3
Supp-examination
1
3
3
Grand Total
7
Projected
self Self study Sessions
Number
Hours
Total
study
time Private study
33
breakdown
Grand Total
160
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
72
C o n t i n u o u s Assignments: 15% Tests: 60% Practical mark: 25%
Assessment (CA) Continuous assessment (CA) : Overall assessment (OA) = 60 : 40.
Examination
Written examination (WA) : overall assessment (OA) = 40 : 60.
Supplementary
Inorganic Chemistry III
Module Code
Module Name
NQF
Level
Inorganic Chemistry III
7
Lectures/Tutorials per week
Pracs per
week
4 hours (at least 1 hour tutorial): 6 hours
CHE 3103
Contact hours
Content
Syllabus
Credits
Semester
16
Number
weeks
12
1
of N o t i o n a l
hours
160
/ Theory: 1. The chemistry of d-block elements. 2. Structure of Transition
metal compounds. 3.The chemistry of f-block elements. 4.Introduction to
organo-metallic chemistry. 5.Introduction to bio-inorganic chemistry
Learning
and
Teaching
breakdown
Assessment
breakdown
Projected
self
study
time
breakdown
Learning and Teaching Session
Number
Hours
Total
Lectures & Tutorials
12
4
48
Practicals
12
6
72
Total
120
Assessment Sessions
Number
Hours
Total
Tests (All levels)
2
2
4
Assignments
2
Practical reports
6
Examination
1
3
3
Supp-examination
1
3
3
Grand Total
7
Self study Sessions
Number
Hours
Total
Private study
33
Grand Total
160
Assignments: 15% Tests: 60% Practical mark: 25%
Continuous assessment (CA) : Overall assessment (OA) = 60 : 40.
Continuous
Assessment
(CA)
Examination
Written examination (WA) : overall assessment (OA) = 40 : 60.
Organic Chemistry II
Module Code Module Name
CHE 2204
Organic Chemistry
Contact hours Lectures/Tutorials per week
NQF Level
7
Practicals per
week
4 hours (at least 1 hour tutorial): 6 hours
73
Credits
16
Number
of weeks
12
Semester
1
Notional
hours
160
2014
PROSPECTUS
Content /
Syllabus
Learning
and
Teaching
breakdown
Assessment
breakdown
Projected self
study time
breakdown
Continuous
Assessment
(CA)
Examination
Theory: 1.Basic Introduction and Revision 2. Stereo- and Alicyclic Chemistry
3. Nucleophilic substitution Reactions 4. Electrophilic substitution Reactions
5. Molecular Rearrangements, 6. Oxidation Reactions 7. Reduction
Reactions 8. Spectroscopic Methods in Organic Synthesis
Learning and Teaching Session
Number
Hours
Total
Lectures & Tutorials
12
4
48
Practicals
12
6
72
Total
120
Assessment Sessions
Number
Hours
Total
Tests (All levels)
2
2
4
Assignments
2
Practical reports
6
Examination
1
3
3
Supp-examination
1
3
3
Grand Total
7
Self study Sessions
Number
Hours
Total
Private study
33
Grand Total
160
Assignments: 15% Tests: 60% Practical mark: 25%
Continuous assessment (CA) : Overall assessment (OA) = 60 : 40.
Written examination (WA) : overall assessment (OA) = 40 : 60.
Organic Chemistry III
Module Code Module Name
NQF
Level
CHE3104
Organic Chemistry III
7
Contact hours Lectures/Tutorials per week
Pracs per
week
6 hours (at least 1 hour tutorial) 6 hours
Content
Syllabus
Outcomes
Credits
Semester
16
Number
weeks
12
1
of Notional hours
160
/ Theory: 1. Groups Protection in Organic Synthesis 2. Alkylation of Carbanions
3. Formation of C-C bonds by base-catalysed Condensations 4. Formation of
C-C bonds by acid-catalysed Condensations 5. The Wittig Reaction 6. Cycloaddition Reactions (with emphasis on Diels-Alder Reaction) 7. Oxidations 9.
Reductions 10. Further Aromatic Chemistry 11. Heterocyclic Chemistry 12.
Basic Theory of NMR (both 1H and 13C NMR).
After this course the student is expected to be able to: have deep understanding
of organic chemistry in general and organic synthesis in particular, design a
method for the preparation of a given compound, recognize named reactions,
read and understand literature preparative protocols, interpret NMR spectra
to find the structure and predict NMR spectra for a substance
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
74
Learning
and
Teaching
breakdown
Assessment
breakdown
Projected self
study
time
breakdown
Learning and Teaching Session
Number
Hours
Total
Lectures & Tutorials
12
4
48
Practicals
12
6
72
Total Year
120
Assessment Sessions
Number
Hours
Total
Tests
2
2
4
Assignments
2
Practical reports
6
Examination
1
3
3
Supp-examination
1
3
3
Grand Total
7
Self study Sessions
Number
Hours
Total
Private study
33
Grand Total
160
Assignments: 15% Tests: 60% Practical mark: 25%
Continuous assessment (CA) : Overall assessment (OA) = 60 : 40.
Continuous
Assessment
(CA)
Examination
Written examination (WA) : overall assessment (OA) = 40 : 60.
Physical Chemistry II
Module Code
CHE 2105
Contact hours
Module Name
Physical Chemistry II
Lectures/Tutorials per week
4 hours (+ at least 1 hour
tutorial):
75
NQF Level
7
Practicals per
week
6 hours
Credits
16
Number of
weeks
12
Semester
1
Notional
hours
160
2014
PROSPECTUS
Content /
Syllabus
Learning
and
Teaching
breakdown
Assessment
breakdown
Projected self
study time
breakdown
Continuous
Assessment
(CA)
Examination
Theory: 1.Introduction: units, mathematical review. 2. The First Law of
Thermodynamics: Heat, Work, the First Law. 3. Applying the First Law: Heat
Capacities, Isothermal and Adiabatic Changes, Reversible and Irreversible
Processes. 4. Thermochemistry: Heats of Reaction, Temperature Dependence
of Reaction Enthalpies, Heat and Physical Changes. 5. The Second and Third
Law of Thermodynamics: Heat Engines, Carnot Cycle, Entropy, Entropy
Calculations and Absolute Entropies, the Third Law. 6. Work, free Energy
and Chemical Equilibrium: Maximum Work, Free Energy, Thermodynamic
Relations and their Manipulations. 7. The Equilibrium Constants for Ideal
Gas Reactions. 8. Equilibrium Constants for Real Gases: Real Gas Behaviour,
Van Der Waals Equation, Fugacity, Equilibrium Constants. 9. Phase
Equilibrium: Stability of Phases, the Phase Rule, One-Component Systems,
Slopes on a Phase Diagram; the Clapeyron Equation. 10. Colligative
Properties of Ideal Solutions: Solutions, Raoult’s Law: the Ideal Solution.,
Partial Molar Quantities, Mixing of Ideal Solutions, Dilute Solutions and
Henry’s Law, Activities, Osmotic Pressure, Freezing Point Depression and
Boiling Point Elevation. 11. Electrochemical Cells: Classification, EMF and
Electrode Potentials, Half-Cells, the Nernst Equation, Thermodynamic Data
from Cell EMF’s. 12. Chemical Kinetics: The Concept of Rate of Reaction,
Empirical Order of Reaction: Zero, First and Second-Order Reactions, HalfLives,Determining the Order of Reaction.
Learning and Teaching Session
Number Hours
Total
Lectures & Tutorials
12
4
48
Practicals
12
6
72
Total
120
Assessment Sessions
Number Hours
Total
Tests (All levels)
2
2
4
Assignments
2
Practical reports
6
Examination
1
3
3
Supp-examination
1
3
3
Grand Total
7
Self study Sessions
Number Hours
Total
Private study
33
Grand Total
160
Assignments: 20% Tests: 40% Practical mark: 40%
Continuous assessment (CA) : Overall assessment (OA) = 60 : 40.
Written examination (WA) : overall assessment (OA) = 40 : 60.
Physical Chemistry III
Module Code
CHE 3205
Contact hours
Module Name
Physical Chemistry III
Lectures/Tutorials
per
week
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
76
NQF Level
Credits Semester
7
16
1
Practicals per N u m b e r
week
of weeks Notional hours
4 hours (+ at least 1
hour tutorial):
6 hours
12
160
Content / Syllabus
Theory: 1. Reaction Mechanisms: the Concept of a Mechanism,
Opposing Reactions and Equilibrium Constants, Consecutive and Parallel
Reactions, Rate–Determining Step and Steady- State Approaches,
Complex Reactions. 2. Theoretical Approaches to Chemical Kinetics:
Temperature Dependence of Reaction Rate, the Collision Theory, the
Activated Complex Theory, Unimolecular Reactions and the Lindemann
Theory. 3. Surface Work: Surface Tension and Surface Energy, Bubbles
and Drops, the Kelvin Equation, Gibbs Formulation for Adsorption,
the Langmuir Adsorption Isotherm. 4. Matter and Waves: Simple
Harmonic Motion, Wave Motion, Standing Waves, Blackbody Radiation
and the Nuclear Atom, the Photoelectric Effect, Spectroscopy and the
Bohr Atom, the De Broglie Relation. 5. Quantum Mechanics: the
Schrodinger Equation, Postulates of Quantum Mechanics, Operators,
Solutions of Schrodinger Equation: the Free Particle, the Particle in a
Ring of Constant Potential , the Particle in a Box, the Particle in a Box
with One Finite Wall; Tunneling. 6. Rotations and Vibrations of Atoms
and Molecules: the Harmonic Oscillator: the Nature of the Harmonic
Oscillator Wavefunctions, the Thermodynamics of Harmonic Oscillator
Wavefunctions, the Rigid Diatomic Rotor, the Thermodynamics of the
rigid Rotor.
Learning
Learning and Teaching Session Number
Hours
Total
and
Lectures & Tutorials
12
4
48
Teaching
Practicals
12
6
72
breakdown
Total
120
Assessment
Assessment Sessions
Number
Hours
Total
breakdown
2
2
Tests (All levels)
4
Assignments
2
Practical reports
6
Examination
1
3
3
Supp-examination
1
3
3
Grand Total
7
Projected self study Self study Sessions
Number
Hours
Total
time breakdown
Private study
33
Grand Total
160
Continuous
Assignments: 20% Tests: 40% Practical mark: 40%
Assessment (CA)
Continuous assessment (CA) : Overall assessment (OA) = 60 : 40.
Examination
Written examination (WA) : overall assessment (OA) = 40 : 60. Student
must obtain a term mark of at least 40% and an exam mark of at least
40% to qualify for a supplementary
77
2014
PROSPECTUS
Extended General Physics I
Code
PHY1111
Lectures per week
Course
Practicals per week
NQF Level
5
Tutorials per
week
1 x 50 min
Credits
16
Number of
weeks
15
Semester
1
Notional hrs
4 x 50 min
1 x 150 min
160
Content / Syllabus:
Science – a way of knowing; Measurements in Physics; Kinematics; Dynamics; Kinetic
Theory, Properties of Matter & Modern Physics
Assessment:
Continuous Assessment mark : To qualify for examinations, student must attain 40%
continuous assessment mark (CAS 100% = 50% from major tests + 30% from practicals
+ 20% from tutorials, other assessments & assignments). The contribution of CAS mark to
Semester mark is 60%.
Examination Mark : Paper I Theory (60%) + Paper II Practical (40%) = 100%.
To qualify for overall assessment of semester mark, the student must obtain a minimum
examination mark of 40%.
The contribution of examination mark to semester mark is 40%.
Overall Semester mark : 60% CAS + 40% Exam mark.
To qualify for module credit (16), student must obtain a minimum of 50% semester mark.
Supplementary Examination : To qualify for this, a student must obtain a semester mark of
40% - 49%
Entry Assumptions/Pre-requisites:
NSC – qualified to progress to a diploma course - achievement rating of 3(40-49%) or better
in 4 recognized content 20 credit subjects including Mathematics & Physical science. Rating
2 in English & Life Skills.
Matriculation : Senior Certificate with a minimum of E(HG)/D(SG) in Mathematics & Physical
Science. E(SG) in English.
Other requirements : Minimum achievement of 3 in SATAP tests in English, Mathematics &
Science.
Co-requisite : MAT1111
Extended General Physics II
Code
PHY1212
Lectures per week
Course
NQF Level
Credits
Semester
5
16
2
Practicals per week Tutorials per week Number of weeks Notional
hrs
1 x 150 min
1 x 50 min
15
160
4 x 50 min
Content / Syllabus:
Thermodynamics; Magnetism, Static & Current Electricity; Electromagnetism; Wave theory,
Longitudinal Sound waves; Electromagnetic waves, Light & Optics
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
78
Assessment:
Continuous Assessment mark : To qualify for examinations, student must attain 40%
continuous assessment mark (CAS 100% = 50% from major tests + 30% from practicals
+ 20% from tutorials, other assessments & assignments). The contribution of CAS mark to
Semester mark is 60%.
Examination Mark : Paper I Theory (60%) + Paper II Practical (40%) = 100%.
To qualify for overall assessment of semester mark, the student must obtain a minimum
examination mark of 40%.
The contribution of examination mark to semester mark is 40%.
Overall Semester mark : 60% CAS + 40% Exam mark.
To qualify for module credit (16), student must obtain a minimum of 50% semester mark.
Supplementary Examination : To qualify for this, a student must obtain a semester mark of
40% - 49%
Entry Assumptions/Pre-requisites:
NSC – qualified to progress to a diploma course - achievement rating of 3(40-49%) or
better in 4 recognized content 20 credit subjects including Mathematics & Physical science.
Rating 2 in English & Life Skills.
Matriculation : Senior Certificate with a minimum of E(HG)/D(SG) in Mathematics & Physical
Science. E(SG) in English.
Other requirements : Minimum achievement of 3 in SATAP tests in English, Mathematics &
Science.
Co-requisite : MAT1212
Extended General Physics III
Code
Course
NQF Level
Credits
Semester
PHY1113
5
16
1
Lectures per week Practicals per week Tutorials per week Number of weeks N o t i o n a l
hrs
4 x 50 min
1 x 150 min
1 x 50 min
15
160
Content / Syllabus:
Vectors; Motion in 2 or 3 dimensions; Newton’s Laws; Circular Motion; Energy transfer; Linear
Momentum & collisions; Static Equilibrium & elasticity; Temperature & heat; Kinetic theory of
Gases; Heat engines, entropy & second law of thermodynamics
Assessment:
Continuous Assessment mark : To qualify for examinations, student must attain 40%
continuous assessment mark (CAS 100% = 50% from major tests + 30% from practicals
+ 20% from tutorials, other assessments & assignments). The contribution of CAS mark to
Semester mark is 60%.
Examination Mark : Paper I Theory (60%) + Paper II Practical (40%) = 100%.
To qualify for overall assessment of semester mark, the student must obtain a minimum
examination mark of 40%.
The contribution of examination mark to semester mark is 40%.
Overall Semester mark : 60% CAS + 40% Exam mark.
To qualify for module credit (16), student must obtain a minimum of 50% semester mark.
Supplementary Examination : To qualify for this, a student must obtain a semester mark of
40% - 49%
79
2014
PROSPECTUS
Entry Assumptions/Pre-requisites:
A pass in PHY1111, PHY1212, MAT1111 & MAT1212
Co-requisite : MAT1113
Extended General Physics IV
Code
Course
NQF Level
Credits
Semester
PHY1214
5
16
2
Lectures per week Practicals per week Tutorials per week Number of weeks N o t i o n a l
hrs
4 x 50 min
1 x 150 min
1 x 50 min
15
160
Content / Syllabus:
Wave motion; Sound waves; Superposition & standing waves; Electric fields; Gauss’s law;
Electric potential;
Capacitance & Dielectrics; Direct current circuits; Magnetism
Assessment:
Continuous Assessment mark : To qualify for examinations, student must attain 40%
continuous assessment mark (CAS 100% = 50% from major tests + 30% from practicals
+ 20% from tutorials, other assessments & assignments). The contribution of CAS mark to
Semester mark is 60%.
Examination Mark : Paper I Theory (60%) + Paper II Practical (40%) = 100%.
To qualify for overall assessment of semester mark, the student must obtain a minimum
examination mark of 40%.
The contribution of examination mark to semester mark is 40%.
Overall Semester mark : 60% CAS + 40% Exam mark.
To qualify for module credit (16), student must obtain a minimum of 50% semester mark.
Supplementary Examination : To qualify for this, a student must obtain a semester mark of
40% - 49%
Entry Assumptions/Pre-requisites:
A pass in PHY1111, PHY1212, MAT1111 & MAT1212
Co-requisite : MAT1214
General Physics I
Code
Course
NQF Level
Credits
Semester
PHY 1101
5
16
1
Lectures per week Practicals per week Tutorials per week Number of weeks Notional hrs
4 x 50 min
1 x 180 min
1 x 50 min
15
160
Content / Syllabus:
Introduction to Mechanics: Rectilinear Motion; Vector Algebra and Calculus; Motion in two
and Three Dimensions; Newton’s laws; Gravitational force and friction; Statics and Elasticity;
Circular motion and other applications of Newton’s Laws; Work, energy and power; Potential
energy and conservation of energy; Linear momentum and collisions; Rotation of a rigid
object about a fixed axis; Rolling motion; angular momentum and torque; Oscillatory motion;
Fluid mechanics.
Heat and Thermodynamics: Temperature; Heat and the First Law of Thermodynamics; Kinetic
Theory of Gases; Heat, Energy; Entropy and Second Law of Thermodynamics
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
80
Assessment:
Continuous Assessment Mark: To qualify for an end of semester examination, a candidate
must attain at least a 40% continuous Assessment mark (CASS 100% = 50% from Major
Tests + 30% Practical Assessment + 20% from tutorials, minor tests and other Assignments).
Examination Mark: End of Semester Examination: 100% (a candidate should obtain a
minimum of 40%)
Overall Semester Mark: Final Semester Mark: 0.6 Continuous Assessment Mark + 0.4
Examination Mark.
Classification of Performance: Award of Module Credits: To qualify for the award of 16 credits,
a candidate must obtain a minimum of 50% in the overall Semester Mark.
Supplementary Examination: To qualify to sit for this, a candidate should have obtained a
semester mark of 40%-49%.
Entry Assumptions/Pre-requisites: To register for this course, a candidate should have passed
NSC with a “B” designation or equivalent. In addition, a grade of at least 4 should have been
obtained in Mathematics and Physical Science.
General Physics II
Code
Course
NQF Level
Credits
Semester
PHY 1202
5
16
1
Lectures per week Practicals per week Tutorials per week Number of weeks N o t i o n a l
hrs
4 x 50 min
1 x 180 min
1 x 50 min
15
160
Content / Syllabus:
Mechanical Waves: Wave motion; Sound waves; Superposition and Standing waves
Geometrical Optics: The nature of light and laws of Geometric Optics.
Electromagnetism: Electrostatics; Electric Potential, Gauss’ s Law; Capacitance and Dielectrics,
Current and Resistance, Direct Current Circuits; Magnetic Fields and Forces; Induced Fields
and Forces.
Assessment:
Continuous Assessment Mark: To qualify for an end of semester examination, a candidate
must attain at least a 40% continuous Assessment mark (CASS 100% = 50% from Major
Tests + 30% Practical Assessment + 20% from tutorials, minor tests and other Assignments).
Examination Mark: End of Semester Examination: 100% (a candidate should obtain a
minimum of 40%)
Overall Semester Mark: Final Semester Mark: 0.6 Continuous Assessment Mark + 0.4
Examination Mark.
Classification of Performance: Award of Module Credits: To qualify for the award of 16 credits,
a candidate must obtain a minimum of 50% in the overall Semester Mark.
Supplementary Examination: To qualify to sit for this, a candidate should have obtained a
semester mark of 40%-49%.
Entry Assumptions/Pre-requisites: To register for this course, a candidate should have passed
NSC with a “B” designation or equivalent. In addition, a grade of at least 4 should have been
obtained in Mathematics and Physical Science.
81
2014
PROSPECTUS
Code
Course
NQF Level
Credits
Semester
PHY2101
Mechanics & Waves 6
16
1
Lectures per week Practicals per week Tutorials per week Number of weeks N o t i o n a l
hrs
4 x 50 min
1 x 180 min
2 x 40 min
15
160
Content / Syllabus: Vector fundamentals; Rectilinear motion of a particle; Position dependent
forces; The Harmonic oscillator; The general motion of a particle in three dimensions; Central
forces; Dynamics of systems of particles; Coupled oscillators; The wave equation.
Assessment: Modules mark (M) will be obtained from continuous assessment based on
quizzes, tutorials, lab reports, and tests. The final mark will be obtained from the Module
mark (M) and Summative Assessment (E) in the ratio 3:2.
Entry Assumptions/Pre-requisites: PHY1101, PHY1202, MAT1101, MAT1201
Co-requisites: MAT2101, MAT2201
Thermodynamics and Modern Physics
Code
Course
NQF Level
Credits
Semester
PHY2202
Lectures per week
6
16
2
Practicals per week Tutorials per week Number of weeks N o t i o n a l
hrs
1 x 180 min
2 x 40 min
15
160
4 x 50 min
Content / Syllabus:
Thermodynamics
Temperature, reversible processes and work, The First Law of thermodynamics, The Second
Law of Thermodynamics, Entropy, The thermodynamic Potentials and the Maxwell relations,
General thermodynamics relations, Change of phase, Open systems and the Chemical
Potential, The third law of Thermodynamics.
Modern Physics
Atoms and Kinetic Theory (Atomic Theory of Matter, Kinetic Theory, Specific Heat of gases,
The Maxwell Distribution of Velocities and Brownian Motion). Elementary Particles (Discovery
of the electron, quantization of electric charge, the photon, neutron, antiparticles and spin,
discovery of X-rays). The Quantum Theory of Light (Blackbody Radiation, The RayleighJeans Theory, Planck’s Theory of Radiation, Einstein’s transition Probabilities, Amplification
through Stimulated emission, the Ruby and Neon Lasers). The Particle Nature of Photons
(The Photoelectric Effect, The Compton Effect, The Dual Nature of Photons, the Wave Packet,
The Uncertainty Principle).
The Quantum Theory of Atom (Models of Thomson and Rutherford, Classical Scattering
Cross-section, Bohr’s Theory of Atomic Spectra, The Franck-Hertz Experiment, X-ray Spectra
and the Bohr Theory). Nuclear Physics (Binding Energy, Radioactivity, Nuclear Reactions,
Nuclear fusion and fission). Nuclear Physics (Space-time and dynamics, relativity of mass,
length contraction and time dilation).
Assessment: Modules mark (M) will be obtained from continuous assessment based on
quizzes, tutorials, lab reports, and tests. The final mark will be obtained from the Module
mark (M) and Summative Assessment (E) in the ratio 3:2.
Entry Assumptions/Pre-requisites: PHY1101, PHY1202, MAT1101, MAT1201
Co-requisites: MAT2101, MAT2201
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
82
Electromagnetism & Quantum Mechanics
Code
Course
NQF Level
Credits
Semester
PHY3101
7
24
1
Lectures per week Laboratory
Tutorials per week Number of weeks Notional hours
sessions per
week
4 x 50 min
2 x 180 min
2 x 50 min
15
240
Content / Syllabus:
ELECTROMAGNETISM: Vector analysis: Gradient, divergence and curl, fundamental theorems
of calculus, Laplacian, curvilinear coordinate systems: Cartesian, cylindrical and spherical
Coulomb’s law and electric scalar charges, electric fields and scalar potentials of distributed
electric scalar charges: direct integration and Gauss’ law, Poisson’s and Laplace’s equations,
equipotential surfaces, electric conductors
Biot-Savart law and magnetic sources, magnetic fields and vector potentials, magnetic forces,
magnetic fields by direct integration and Ampere’s circuital law, Faraday’s law and induced emf
Electric and magnetic dipole moments and polarizations, linear isotropic and homogeneous
media, electric and magnetic fields due to polarized media, hysteresis, Maxwell’s equations,
boundary conditions
QUANTUM MECHANICS: Statistical interpretation of the double-slit interference experiment;
Derivation of the Schrödinger equation for a force-free region; Separation of the Schrödinger
equation; Conditions of good behaviour for wave functions; Simple barrier problems; One
dimensional potential well of infinite height; Two and three-dimensional problems, degeneracy;
Parity; Graphical nature of wave functions; Operators in Quantum Mechanics; The harmonic
oscillator; The hydrogen atom; Heisenberg Uncertainty Principle.
Assessment: Modules mark (M) will be obtained from continuous assessment based on
quizzes, tutorials, lab reports, and tests. The final mark will be obtained from the Module
mark (M) and Summative Assessment (E) in the ratio 3:2.
Entry Assumptions/Pre-requisites: PHY2101, PHY2202, MAT2101, MAT2102, MAT2201,
MAT2202
Co-requisites: None
83
2014
PROSPECTUS
Statistical Mechanics & Solid State Physics
Code
Course
NQF Level
Credits
Semester
PHY3202
7
24
2
Lectures per week L a b o r a t o r y Tutorials per week Number of weeks Notional hrs
sessions per week
4 x 50 min
2 x 180 min
2 x 50 min
15
240
Content / Syllabus:
STATISTICAL MECHANICS: Statistical equilibrium; The Maxwell-Boltzmann distribution
law; Thermal equilibrium; Application to Ideal gas; Entropy and heat in terms of statistical
probability; Heat capacity of ideal monatomic and an ideal polyatomic gas; The principle of
equipartition of energy; The Einstein Solid; Fermi-Dirac distribution law; The electron gas;
Application of Fermi-Dirac statistics to electrons in metals; Bose-Einstein distribution law; The
photon gas; Heat capacities of vibrating molecules and of solid bodies.
SOLID STATE PHYSICS: Crystals: binding, structure, defects and growing techniques. Lattices
dynamics: quantized vibrations, phonons and density of states, specific heat capacity and
Debye law. Free electron theory of metals: density of states, specific heat capacity, electrical
conductivity and Hall effect, Pauli paramagnetism, thermionic emission. Comparison of metals,
insulators, semimetals and semiconductors, band structure. Magnetic properties of materials:
types of magnetism, susceptibility and permeability. Dielectrics: polarization, temperature
and frequency dependence of permittivity, ferroelectric and piezoelectric materials.
Semiconductors: holes and conduction electrons, intrinsic and extrinsic semiconductors,
donors and acceptors, temperature dependency of electrical conductivity
Assessment: Modules mark (M) will be obtained from continuous assessment based on quizzes,
tutorials, seminar presentations, lab reports, and tests. The final mark will be obtained from
the Module mark (M) and Summative Assessment (E) in the ratio 3:2.
Entry Assumptions/Pre-requisites: PHY2101, PHY2202, MAT2101, MAT2102, MAT2201,
MAT2202
Co-requisites: None
Introduction to Object Oriented Programming
Module Code
CSI 1201
Lectures per week
1 x 2 hrs
Content / Syllabus
Learning
and
Teaching
breakdown
Module Name NQF Level
Credits
Semester
5
8
2
Pracs per week Tutorials per week Number of weeks N o t i o n a l
hours
1 x 3 hrs(x 2 1 x 1hrs (x 2 14
84
groups)
groups)
Theory: Classes, Objects and data abstraction, Inheritance,
polymorphism, Pointers, virtual functions, templates, exception handling.
Learning and Teaching Session
Lectures
Practicals
Tutorials
Grand Total
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
84
Number
14
14
14
Hours
2
3
1
Total
28
56
14
84
Assessment
breakdown
Assessment Sessions
Number
Hours
Total
Major tests
2
2
4
Practical Assessment
12
1
12
Assignments
2
2
4
Tutorial assignments
12
1
12
Summative assessment
Examination
1
3
3
Re-examination (optional)
Special examination (optional)
Oral examination (optional)
Grand Total
35
Projected self study Self study Sessions
Number
Hours
Total
time breakdown
Private study
28
1
28
Group work
28
.5
14
Pre-assessment revision
12
.2
2.4
Grand Total
44.4
Entry
MATRICULATION: Qualified for bachelors. At least 3 in mathematics, 2
rules
in English and 2 in life orientation.
REQUIRED NSC SUBJECTS (Compulsory): Mathematics, English
Recommended: IT, CAT
OTHER (SATAP): 3 in mathematics, (Should have cleared CSI1111 &
CSI1212)
Assessment
Continuous Assessment (CA) (Compulsory): Two Assignments(30%),
and progression
Two Tests (40%), 12 tutorial assessments(10%) and 12 Practical
rules
assessments(20%)
Examination (Compulsory): One examination (EA). The contribution of
the examination (EA) to the overall assessment (OA) is 40%. OA =
60%(CA) + 40%(EA).
Re-examination (Not compulsory): To qualify for re-examination students
must obtain an overall assessment of between 40 and 49%.
Exclusion from
NA
module
Introduction to Information Systems
Module Code
CSI 1101
Lectures per
week
1 x 2 hrs
Module Name NQF Level
Credits
Semester
5
8
1
Pracs per week Tutorials per week Number of weeks Notional hours
0
2 x 2hrs (x 2
groups)
85
14
84
2014
PROSPECTUS
Content / Syllabus Theory: Fundamentals of IS, Data and Information; Importance of
Information Systems; Computer Based Information Systems, Information
System Requirements: Input, Process, Output, Information Systems as
seen by the user, End-User Computing Applications; Office Automation;
Distributed computing Hardware Fundamentals, Software Fundamentals, User Interfaces,
Command driven interfaces; Menu driven interfaces; Icon and pointer
based interfaces, Operating Systems; Applications Software; Programming
languages, Developing Information Systems, The classic systems
development life cycle
Business Information Systems, Transactions Processing, Management
Information Systems, Decision Support Systems, Expert Systems
Learning
Learning and Teaching Session
Number
Hours
Total
and
Lectures
14
2
28
Teaching
Practicals
0
0
0
breakdown
Tutorials
28
2
56
Grand Total
84
Assessment
Assessment Sessions
Number
Hours
Total
breakdown
Major tests
2
2
4
Practical Assessment
Assignments
2
2
4
Tutorial assignments
12
1
12
Summative assessment
Examination
1
3
3
Re-examination (optional)
Special examination (optional)
Oral examination (optional)
Grand Total
23
Self study Sessions
Number
Hours
Total
Projected self
study time
Private study
28
1
28
breakdown
Group work
28
.5
14
Pre-assessment revision
12
.2
2.4
Grand Total
44.4
Entry
MATRICULATION: Qualified for bachelors. At least 3 in mathematics, 2 in
rules
English and 2 in life orientation.
REQUIRED NSC SUBJECTS (Compulsory): Mathematics, English
Recommended: IT, CAT
OTHER (SATAP): 3 in mathematics,
Continuous Assessment (CA) (Compulsory): Two Assignments(40%), Two
Assessment
Tests (40%), 12 tutorial assessments(20%)
and progression
rules
Examination (Compulsory): One examination (EA). The contribution
of the examination (EA) to the overall assessment (OA) is 40%. OA =
60%(CA) + 40%(EA).
Re-examination (Not compulsory): To qualify for re-examination students
must obtain an overall assessment of between 40 and 49%.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
86
Exclusion from
module
NA
Introduction to Information Systems
Module Code
Module Name
CSI 1101
Lectures per week Pracs per week
1 x 2 hrs
0
NQF Level
Credits
Semester
5
8
1
Tutorials per week Number of weeks Notional hours
2 x 2hrs (x 2 14
84
groups)
Content / Syllabus Theory: Fundamentals of IS, Data and Information; Importance of
Information Systems; Computer Based Information Systems, Information
System Requirements: Input, Process, Output, Information Systems as
seen by the user, End-User Computing Applications; Office Automation;
Distributed computing Hardware Fundamentals, Software Fundamentals, User Interfaces,
Command driven interfaces; Menu driven interfaces; Icon and
pointer based interfaces, Operating Systems; Applications Software;
Programming languages, Developing Information Systems, The classic
systems development life cycle
Business Information Systems, Transactions Processing, Management
Information Systems, Decision Support Systems, Expert Systems
Learning
and
Teaching
breakdown
Assessment
breakdown
Projected self
study time
breakdown
Learning and Teaching Session
Lectures
Practicals
Tutorials
Grand Total
Assessment Sessions
Major tests
Practical Assessment
Assignments
Tutorial assignments
Summative assessment
Examination
Re-examination (optional)
Special examination (optional)
Oral examination (optional)
Grand Total
Self study Sessions
Private study
Group work
Pre-assessment revision
Grand Total
87
Number
14
0
28
Hours
2
0
2
Number
2
Hours
2
Total
28
0
56
84
Total
4
2
12
2
1
4
12
1
3
3
Number
28
28
12
Hours
1
.5
.2
23
Total
28
14
2.4
44.4
2014
PROSPECTUS
Entry
rules
Assessment
and progression
rules
Exclusion from
module
MATRICULATION: Qualified for bachelors. At least 3 in mathematics, 2
in English and 2 in life orientation.
REQUIRED NSC SUBJECTS (Compulsory): Mathematics, English
Recommended: IT, CAT
OTHER (SATAP): 3 in mathematics,
Continuous Assessment (CA) (Compulsory): Two Assignments(40%),
Two Tests (40%), 12 tutorial assessments(20%)
Examination (Compulsory): One examination (EA). The contribution
of the examination (EA) to the overall assessment (OA) is 40%. OA =
60%(CA) + 40%(EA).
Re-examination (Not compulsory): To qualify for re-examination students
must obtain an overall assessment of between 40 and 49%.
NA
Operating Systems
Module Code
Module Name
NQF Level
CSI 2201
6
Lectures per week Practicals per week Tutorials per
week
1 x 2 hr
1 x 2 hr
Credits
14
Number of weeks
14
Semester
1
Notional
hours
140
Content / Syllabus Theory: Overview of operating systems, functionalities and
characteristics of OS. Hardware concepts related to OS, CPU states,
I/O channels, memory hierarchy, microprogramming, The concept of a
process, operations on processes, process states, concurrent processes,
process control block, process context. Job and processor scheduling,
scheduling algorithms, process hierarchies. Problems of concurrent
processes, critical sections, mutual exclusion. Mutual exclusion,
process co-operation, producer and consumer processes. Semaphores:
definition, init, wait, signal operations. Critical sections Interprocess
Communication (IPC), Message Passing, Direct and Indirect Deadlocks.
Memory organization and management, storage allocation. Virtual
memory concepts, paging and segmentation, address mapping. Virtual
storage management, page replacement strategies. File organization:
blocking and buffering, file descriptor, directory structure File and
Directory structures, blocks and fragments, directory tree, UNIX file
structure. Practicals: Consist of 14 tutorials chosen from each section of
content covered.
Learning
Learning and Teaching Session
Number Hours
Total
and
Lectures
14
2
28
Teaching
Practicals
breakdown
Tutorials
14
2
28
Grand Total
56
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
88
Assessment
breakdown
Projected self
study time
breakdown
Entry
rules
Assessment
and progression
rules
Exclusion from
module
Assessment Sessions
Number Hours
Total
Major tests
3
1
3
Class tests
Assignments
Tutorial assignments
3
6
18
Summative assessment
Examination
1
3
3
Re-examination (optional)
1
3
3
Special examination (optional)
Oral examination (optional)
Grand Total
27
Self study Sessions
Number Hours
Total
Private study
14
4
Group work
Pre-assessment revision
Grand Total
56
MATRICULATION: Entry Requirements for the Science Faculty.
REQUIRED NSC SUBJECTS (Compulsory): Entry Requirements for the
Science Faculty.
RECOMMENDED NSC SUBJECTS (Not compulsory):
OTHER (specify): Pre-requisites: CSI1101, CSI1102, CSI1201and
CSI1202, MAT1101, CSI1102, CSI1203 and MAT1201 or APM1101,
APM1201
Continuous Assessment (CA) (Compulsory): The contribution of CA to
the overall assessment (OA) is 60%.
Examination (Compulsory): One examination (EA). The contribution of
the examination (EA) to the overall assessment (OA) is 40%.
Re-examination (Not compulsory):
Faculty rules apply, whereby the student progresses from a lower level
to the next.
89
2014
PROSPECTUS
Introduction to Artificial Intelligence
Module Code
CSI3101
Lectures per week
3 x 50 min
Contents/Syllabus
Entry Rules
Assessment
and progression
rules
Module Name NQF Level
Credits
Semester
6
14
1
Pracs per week Tutorials per week Number of weeks Notional
hours
1 x 3 hrs
1 x 50 min
14
140
Theory: Introduction to AI , Definitions , Early work-A Historical Overview
, The Turing Test ,Intelligent Agents , The Idea of an Agent , Types of
Agents , Types of Environments, Solving Problems by Search , Problem
Solving agents , Formulating Problems , Searching for Solutions Search
Strategies , Uninformed Search Strategies , Breadth First Search , Depth
First Search , Uniform Cost Path Search , Informed Search Methods ,
Best-First –Search , Greedy Search , A* Search, Game Playing , The 8
Puzzle , The 8 Queens problem , Tic-Tac-Toe, First Order Predicate Logic
, Representation , Reasoning and Logic , Propositional Logic , Syntax and
Semantics , Using First Order Logic, Learning Methods, Neural Networks
and Learning.
Practicals: Consist of 5 labs based on what is covered during lectures.
Applicant must have Passed all Second Year Modules, CSI2202, CSI2102
Continuous Assessment (CA) (Compulsory): Two class tests (CT), five
assignments (AA), three tutorial assignments (TA), a practical assessment
(PA), an examination (EA) and a re-examination (RA).
Examination (Compulsory): One examination (EA). The contribution
of the examination (EA) to the overall assessment (OA) is 40%. OA =
60%(CA) + 40%(EA). To qualify for course credit students must obtain
an overall assessment of 50%.
Re-examination (Not compulsory): To qualify for re-examination students
must obtain an overall assessment of between 40 and 49%.
Software Engineering I
Module Code
Module Name
CSI3102
Lectures per week Pracs per week
3 x 50 min
1 x 3 hrs
NQF Level
Credits
6
14
Tutorials per week Number of weeks
1 x 50 min
14
Semester
1
Notional hours
140
Content / Syllabus Theory: Need for Software Engineering, Problems in software development,
What is software engineering? software process: the waterfall model,
prototyping approaches, evolutionary development models, project
management: scheduling, cost estimation, requirements & design
analysis: requirements engineering, analysis, definition, specification,
requirements document, functional and non-functional requirements,
requirements evolution, ssadm: data flow diagrams, entity relationship
modelling (logical data models), modelling with uml: use-cases, class
diagrams, state diagrams, software design: principles of design, designing
for reusability, adaptability and maintainability, design quality software
architecture, testing: test plans, testing methods, test strategies software
maintenance and evolution.: software change and maintenance, software
re-engineering, software configuration management.
Practicals: Consist of 5 labs based on what is covered during lectures.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
90
Entry
rules
MATRICULATION: Faculty rules apply
REQUIRED NSC SUBJECTS (Compulsory):
RECOMMENDED NSC SUBJECTS (Not compulsory):
OTHER (specify): Applicant must have Passed all Second Year Modules,
CSI2202, CSI2102
Assessment
Continuous Assessment (CA) (Compulsory): Two class tests (CT), five
and progression
assignments (AA), three tutorial assignments (TA), a practical assessment
rules
(PA), an examination (EA) and a re-examination (RA).
Examination (Compulsory): One examination (EA). The contribution
of the examination (EA) to the overall assessment (OA) is 40%. OA =
60%(CA) + 40%(EA). To qualify for course credit students must obtain
an overall assessment of 50%.
Re-examination (Not compulsory): To qualify for re-examination students
must obtain an overall assessment of between 40 and 49%.
Exclusion
from A student will be excluded from the course after failing the module twice.
module
A student excluded from a course may be re-admitted after presenting a
similar course from another university for credit.
Database Management Systems
Module Code
CSI3201
Lectures per week
Module Name
Pracs per week
NQF Level
7
Tutorials per
week
1 x 50 min
Credits
14
Number of weeks
Semester
1
Notional hours
14
140
3 x 50 min
1 x 3 hrs
Content / Syllabus
Theory: File Systems and Databases, The Relational Database
Model, Structured Query Language (SQL), Entity Relationship (ER) Modeling, Normalisation of Database Tables, Database Design,
Transaction Management and Concurrency Control, Distributed
Database Management System, Object-Oriented Databases, Database
Administration, Database and The Internet.
Practicals: Consist of 5 labs based on what is covered during lectures.
Applicant must have Passed all Second Year Modules, CSI2202,
CSI2102
Continuous Assessment (CA) (Compulsory): Two class tests (CT),
five assignments (AA), three tutorial assignments (TA), a practical
assessment (PA), an examination (EA) and a re-examination (RA).
Examination (Compulsory): One examination (EA). The contribution
of the examination (EA) to the overall assessment (OA) is 40%. OA =
60%(CA) + 40%(EA). To qualify for course credit students must obtain
an overall assessment of 50%.
Re-examination (Not compulsory): To qualify for re-examination
students must obtain an overall assessment of between 40 and 49%.
Entry Rules
Assessment
and progression
rules
91
2014
PROSPECTUS
Software Computing II
Module Code
Module Name NQF Level
Credits
Semester
CSI3202
7
14
1
Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours
3 x 50 min
1 x 3 hrs
1 x 50 min
14
140
Content / Syllabus Theory: Software Computing principles revisited, Downstream software
Computing activities, Internet software Architectures and Technologies,
N-Tier Architectures, CORBA, J2EE and .NET architectures, Web
Services, Design Patterns, GOF design Patterns, Web Architecture
Patterns, UML Object Diagrams, Challenges and Pitfalls of Software
Design, Techniques for design, Design as decision making and
evaluation of trade-offs, Examples taken from Object Oriented Design,
Architecture – Driving forces, Various examples, Code Construction
- UML to code, code to UML, Configuration Management –Source
code control and management , Source code processing , Group work
support, Versions and Variants, CVS, Quality Assurance -Defect costs,
Reliability, Standards, Testing – Types of test, verification and validation,
Black and White Box testing, Test analysis and generation, Metrics –
Examples and uses,
Process and Project metrics, Object orientation metrics.
Practicals: Consist of 5 labs based on what is covered during lectures.
Entry Rules
Applicant must have Passed all Second Year Modules, CSI2202, CSI2102
Assessment
Continuous Assessment (CA) (Compulsory): Two class tests (CT),
and progression
five assignments (AA), three tutorial assignments (TA), a practical
rules
assessment (PA), an examination (EA) and a re-examination (RA).
Examination (Compulsory): One examination (EA). The contribution
of the examination (EA) to the overall assessment (OA) is 40%. OA =
60%(CA) + 40%(EA). To qualify for course credit students must obtain
an overall assessment of 50%.
Re-examination (Not compulsory): To qualify for re-examination
students must obtain an overall assessment of between 40 and 49%.
SCHOOL OF MATHEMATICAL AND
COMPUTATIONAL SCIENCES
92