UNIVERSITY OF KENT
MODULE SPECIFICATION
SECTION 1: MODULE SPECIFICATIONS
1.
Title of the module : Statistics (MA306)
2.
School or partner institution which will be responsible for management of the module
School of Mathematics, Statistics and Actuarial Science
3.
Start date of the module : Ongoing (revised version start date September 2014)
4.
The number of students expected to take the module: 200
5.
Modules to be withdrawn on the introduction of this proposed module and consultation with other
relevant Schools and Faculties regarding the withdrawal
Not applicable
6.
The level of the module (e.g. Certificate [C], Intermediate [I], Honours [H] or Postgraduate [M]): C
7.
The number of credits and the ECTS value which the module represents : 15 (ECTS 7.5)
8.
Which term(s) the module is to be taught in (or other teaching pattern): Spring term
9.
Prerequisite and co-requisite modules:
Prerequisite modules: MA321 (Calculus and Mathematical Modelling), MA322 (Proofs and
Numbers), MA323 (Matrices and Probability) or MA312 (Introduction to Financial Concepts)
There are no co-requisite modules.
10. The programmes of study to which the module contributes
BSc (Hons) Mathematics, BSc (Hons) Mathematics & Statistics, BA (Hons) Mathematics and
Accounting & Finance, BSc (Hons) Financial Mathematics (including programmes with a year in
industry), BSc (Hons) Mathematics with Secondary Education, BSc (Hons) Mathematics with a
Foundation Year, MMath Mathematics, MMathStat Mathematics and Statistics
11. The intended subject specific learning outcomes
On successful completion of this module students will:
a) have gained an understanding of the basic concepts of statistics;
b) have established a framework of core statistical material relevant to their degree
programme, which is also appropriate for later statistics modules students may wish to study
as part of their degree;
c) be proficient in the main statistical ideas and techniques introduced in the course;
d) have some appreciation of ways of examining data, both at the exploratory stage through
graphical representations and numerical summaries, and more formally through
techniques of statistical inference;
e) be able to handle and analyse data using the statistical package MINITAB;
f) have some appreciation of how statistics is used in practice;
g) have an appreciation of how the statistical procedures covered are derived and their
validity.
12. The intended generic learning outcomes
Revision March 2014
1
UNIVERSITY OF KENT
Students who successfully complete this module will:
a) have begun to develop a logical, mathematical approach to solving problems;
b) have enhanced their ability to work with relatively little guidance;
c) have gained organisational and study skills;
d) be able to use information technology for data analysis and presentation.
On successful completion of the module, students will also have improved their key skills in written
communication, numeracy, computing and problem solving.
13. A synopsis of the curriculum
 Graphical representations of data. Stem-and leaf plots. Bar charts. Histograms. Cumulative
frequency plots. Scatterplots. Box-and-whisker plots.
 Numerical summaries of data. Order statistics. Sample mean. Median. Trimmed mean.
Mode. Quartiles. Range. Mean deviation. Sample variance and standard deviation.
 Some distributions widely used in statistics. Normal distribution. 2 distribution. t-distribution. Fdistribution.
 Sampling distributions. Definition. Standard error. Sampling distribution of X . Intuitive
verification of Central Limit Theorem from sampling distributions of the mean from arbitrary
distributions. Sampling distribution of the sample proportion. Sampling distribution of S2 for
normal sample.
 Point estimation. Principles. Unbiased estimators. Bias.
 Interval estimation. Concept. Confidence interval for µ, s2 known. Confidence interval for µ, s2
unknown. Confidence interval for s2 for normal sample. Confidence interval for a proportion
with large n. Choosing the sample size. One-sided confidence intervals.
 Hypothesis testing. Testing hypotheses for µ, s2 known. Type I and II errors. Size. P-values.
One-tailed tests. Power function. Testing hypotheses for µ, s2 unknown. Testing
hypotheses for s2 for normal data. Testing hypotheses for a proportion with large n.
 Two-sample problems. Comparing means with known variances - hypothesis test and
confidence interval. Comparing means with unknown variances - hypothesis tests and
confidence intervals. Inferences about the ratio of 2 variances - hypothesis test and
confidence interval. Inferences for the difference between 2 proportions - hypothesis test
and confidence interval. Paired data.
 Association between variables. Product moment and rank correlation coefficients. Two-way
contingency tables. 2 test of independence.
 Introduction to nonparametric procedures. Sign test. 2 goodness of fit test for fully specified H0.
2 goodness of fit test for more general H0.
14. Indicative Reading List
J. Devore and R. Peck. Introductory Statistics. (West 1990)
F. Daly et al. Elements of Statistics. (The Open University 1995)
G.M. Clarke and D. Cooke. A Basic Course in Statistics. (5th edition. Arnold. 2004)
D.V. Lindley and W.F. Scott. New Cambridge Statistical Tables (2nd edition. C.U.P. 1995)
15. Learning and Teaching Methods, including the nature and number of contact hours and the total
study hours which will be expected of students, and how these relate to achievement of the intended
module learning outcomes.
Number of contact hours: 49, consisting of 36 lectures, supplemented by approximately 3 supervised
computing sessions and 10 supervised exercise classes.
Number of independent learning hours: approximately 101.
Total study hours: 150.

The lectures introduce the students to the basic concepts of statistics. The material is related to
real data at every stage and MINITAB is used to provide statistical computing facilities
for all the material studied. Data description and data summarisation techniques are
studied, together with the main methods of statistical inference.
Revision March 2014
2
UNIVERSITY OF KENT



Lectures contain numerous worked examples to illustrate the theoretical techniques and
concepts in the curriculum. The exercise sheets, which students are expected to attempt, aim to
reinforce the lecture material, in addition to giving students practice in the various statistical
techniques. In addition to the exercise sheets, students also work on several practical
problems for which they need to use MINITAB. These practical problems are intended to
give further reinforcement of the technical material, as well as illustrating how statistics is used in
practice.
Regular examples classes are held during which students work on specified exercises with the
module lecturers and other staff on hand to help with any problems. This provides each
student with one-to-one help when needed.
Students are introduced to MINITAB in the computer sessions. Students work through
worksheets which demonstrate how the statistical techniques introduced in the module can be
implemented in MINITAB. Then MINITAB is used to work on larger practical data analysis
problems.
Subject specific learning outcomes 11(a)-(d),(f),(g) and generic learning outcome 12(a) will be
addressed by lectures. Subject specific learning outcomes 11(a)-(d),(f),(g) and generic learning
outcomes 12(a)-(c) will be addressed by exercise classes. Subject specific learning outcomes
11(a)-(g) and generic learning outcomes 12(a)-(d) will be addressed by computing sessions.
16. Assessment methods and how these relate to testing achievement of the intended module learning
outcomes
The module will be assessed by examination (90%) and coursework (10%).


Examination: One 2-hour written exam in the Summer term. The examination paper will consist
of theoretical, manipulative and numerical problems requiring answers of varying length,
assessing subject specific learning outcomes 11(a)-(g) and generic learning outcomes 12(a)-(c)
Coursework: Exercises will be given on individual components of the syllabus, and
assignments will be set involving selections from those exercises, to be completed
outside contact hours. The exercises consist of questions requiring mathematical
manipulations and solution to numerical problems. Required answers will vary in length.
The coursework mark will be derived from these assignments and will require knowledge of
the statistical material taught during the module, and skill in handling the MINITAB computer
package. The exercises will also assess subject specific learning outcomes 11(a)-(g) and
generic learning outcomes 12(a)-(d), concentrating particularly on the handling and analysis of
data using a statistical package, and the appreciation of the use of statistics in practice.
17. Implications for learning resources, including staff, library, IT and space
As the module is already running, there are no additional resource implications.
18. The School recognises and has embedded the expectations of current disability equality legislation,
and supports students with a declared disability or special educational need in its teaching. Within
this module we will make reasonable adjustments wherever necessary, including additional or
substitute materials, teaching modes or assessment methods for students who have declared and
discussed their learning support needs. Arrangements for students with declared disabilities will be
made on an individual basis, in consultation with the University’s disability/dyslexia support service,
and specialist support will be provided where needed.
19. Campus where module will be delivered: Canterbury
Revision March 2014
3
UNIVERSITY OF KENT
SECTION 2: MODULE IS PART OF A PROGRAMME OF STUDY IN A UNIVERSITY SCHOOL
Statement by the School Director of Learning and Teaching/School Director of Graduate Studies
(as appropriate): "I confirm I have been consulted on the above module proposal and have given advice
on the correct procedures and required content of module proposals"
................................................................
..............................................
Director of Learning and Teaching/Director of
Graduate Studies (delete as applicable)
Date
…………………………………………………
Print Name
Statement by the Head of School: "I confirm that the School has approved the introduction of the
module and, where the module is proposed by School staff, will be responsible for its resourcing"
.................................................................
..............................................
Head of School
Date
…………………………………………………….
Print Name
Module Specification Template
Last updated February 2013
Revision March 2014
4