UNIVERSITY OF KENT
MODULE SPECIFICATION
1.
Title of the module:
An Introduction to Quantitative Social Research (SO410)
2.
School or partner institution which will be responsible for management of the module:
SSPSSR
3.
Start date of the module
September 2015
4.
The number of students expected to take the module
180 (after the new programme in Statistical Social Research begins in 2015, this is expected to rise
to 240)
5.
Modules to be withdrawn on the introduction of this proposed module and consultation with
other relevant Schools and Faculties regarding the withdrawal
Along with another proposed 15-credit module (An introduction to Qualitative Social Research), it
replaces the 30-credit module SO602 (the module outline is not included at this stage as it would be
in Stage 2 of the new programme, Statistical Social Research). We have consulted with the current
SO602 module convenor.
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 credits (7.5 credits ECTS)
8.
Which term(s) the module is to be taught in (or other teaching pattern)
Autumn
9.
Prerequisite and co-requisite modules
None
10. The programmes of study to which the module contributes
MSCi Statistical Social Research
BA Criminology and certain joint degrees (BA Criminology & Sociology, BA Criminology & Social
Policy)
BA Health & Social Care
BA Social Policy (and joint degrees BA Criminology & Social Policy, BA Social Policy & Politics, BA
Sociology & Social Policy)
BA Sociology, BA Sociology with certain years abroad (Finland, Hong Kong), and certain joint
degrees (BA Criminology & Sociology, BA Sociology & Politics, BA Sociology & Social Policy).
Note that this does NOT include joint degrees with programmes outside of the Q-Step initiative (BA
Criminology & Cultural Studies, BA Sociology & Anthropology, BA Sociology & Economics, BA
Sociology & Philosophy), nor BA Sociology with years in Italy or Spain (who have compulsory
language courses).
It will also be available as a wild module throughout the Faculty of Social Sciences and the Faculty of
Humanities (subject to approval from individual programme directors).
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11. The intended subject specific learning outcomes
On successful completion of this module, students will:
11.1. Demonstrate knowledge of validity, reliability and transparency issues when carrying out
statistical analyses;
11.2. Understand the difference between descriptive statistics (i.e. central tendency and
dispersion) and inferential statistics (i.e. correlation, regression);
11.3. Demonstrate an ability to select the correct method of statistical analysis (description,
correlation/association, statistical inference) based on the research question under study,
the study design and data available;
11.4. Demonstrate an ability to read, understand and report/represent (e.g. tables, graphs) the
results of regression analyses;
11.5. Demonstrate an ability to carry out multiple forms of regression analysis with the help of
statistical software (e.g. SPSS, Excel).
11.6. Demonstrate an ability to investigate the assumptions of regression (e.g. heterocedasticity)
and assess whether to take appropriate actions when assumptions are not met (e.g.
remove outliers);
11.7. Understand the underlying principles of causality and main limitations when assessing
causal inference;
11.8. Understand the advantages and limitations of using regression for the study of causality;
12. The intended generic learning outcomes
On successful completion of this module, students will:
12.1. Demonstrate strong quantitative analytical skills that will enable them to examine complex
societal processes and communicate them effectively;
12.2. Understand the strengths and weaknesses of quantitative methods of analysis and apply
sound judgement when selecting the statistical method of analysis;
12.3. Demonstrate proficiency in the use of one or various statistical software packages (e.g.
SPSS)
13. A synopsis of the curriculum
This module aims to develop an understanding of key statistical skills in students on their arrival at
Kent, which they can build on in their further research and substantive modules in their degree.
Learning will be oriented towards:
i.
Assessing the strengths and limitations of using regression analysis for the establishment of
causal inference; This includes:
o Distinction between causality, correlation or association
o Levels of measurement (e.g. nominal, ordinal, interval, ratio)
o Methods of regression analysis (e.g. OLS and logistic regression) and related
assumptions
ii.
Learning how to respond to research questions with the application of statistical methods of
analysis, mainly regression methods, with the help of statistical software.
iii.
Learning how to interpret the outcome of regression models and contextualise the results
within broader theories.
14. Indicative Reading List
Allison, P.D. (1999), Multiple Regression: A Primer. Thousand Oaks: SAGE Publications
Agresti, A. (2013). Categorical Data Analysis. Hoboken: Wiley
Bryman, A (2008). Social Research Methods. Oxford: Oxford University Press
Babbie (2010) The Practice of Social Research. Stanford: Cengage Learning
Blastland, M. & Dilnot, A. (2007) The Tiger That Isn’t. London: Profile Books
Cook, T., & Campbell, D. (1979) Quasi-experimentation: Design and analysis issues for field settings.
Chicago: Rand McNally College Publications
Della Porta & Keating (2008) Approaches and Methodologies in the Social Sciences. Cambridge:
Cambridge University Press
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Diamond, I & Jefferies, J (2000). Beginning statistics : an introduction for social scientists. London: SAGE
Field, A. P. (2009) Discovering statistics using SPSS: (and sex and drugs and rock 'n' roll). Thousand
Oaks: SAGE Publications
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
Contact hours: the course will be delivered over 11 weeks, with students receiving at least two hours
of contact time per week. While the format of the contact time will vary depending on the topic, it will
tend to consist of either a 1-hour lecture + 1-hour hands-on data analysis seminar, or a 2-hour data
analysis workshop.
Study hours: beyond contact time (22 hours), students will be expected to do 128 hours of
independent study (approximately 10 hours per week) to meet the total 150 hours of study expected
for a 15-credit module. This will include preparatory and follow up reading and research for lectures
and seminars as well as work towards assessment.
Learning and Teaching Methods:
Lectures
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12.1
12.2
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Seminar /
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Independent
reading & research
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16. Assessment methods and how these relate to testing achievement of the intended module
learning outcomes
Students will be assessed in three ways:
i.
Class participation (5%). Students will be assessed on their participation in class, focusing
in particular on their contribution to in-class debates, preparing appropriately for the classes,
and doing (and putting the requisite effort into) formative assignments. (Seminar leaders will
keep a week-by-week record of students’ preparation and contributions, based on
instructions provided by the module convenor). This will NOT assess students simply on the
basis of their attendance. This component will assess learning outcomes 11.1-11.7 and
12.1-12.3.
ii.
Answer a research question with statistics – Group presentation (40%). Each group will give
an in-class presentation on a research question of their choice where they analyse the
relationship between two factors (or variables) and try to assess the (causal) relationship or
association between these two variables, before and after the incorporation of a control
variable. This will require setting some hypotheses, manipulating some data, carrying out
very simple analyses and presenting the results with the use of causal diagrams. Students
will be assessed on their ability to understand principles of causality, and the way in which
they can present this clearly, linked to wider social theories. This component will assess
learning outcomes 11.1, 11.2, 11.3, 11.4, 11.5, 11.6, 11.7, and 12.1, 12.2.
iii.
Personal study – Report (55%). Students will write a 2500 word report trying to answer a
research question. Students will be required to conduct a literature review, operationalise
concepts, select the relevant variables for analysis and the statistical method, carry out the
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analysis and report the outcomes of the analysis. In all steps the student will be required to
report on the limitations of the study. This component will assess learning outcomes 11.111.8 and 12.1-12.3.
A number of measures will be put in place to discourage limited participation in group work
activities and ensure students are meeting the required learning outcomes. These will include
requiring students to do some group work within seminars (with the seminar leader moving from
group-to-group to examine each person’s participation), allocating students to groups in ways that
discourage free-riding, explicitly teaching students about group work and the penalties for freeriding, giving students responsibility for discouraging free-riding in their group, allowing students
to raise concerns about ‘free-riding’ peers, requiring all students to play some part in the
presentation/Q&A and giving them different marks where appropriate (where applicable), and
requiring a printed version of the slides with an appendix detailing the contribution of each
individual in the group.
17. Implications for learning resources, including staff, library, IT and space
This module replaces SO602, and the learning resources required will be similar. Some additional
materials may be required to update and extend existing resources. These purchases will be made
from SPSSR’s annual Canterbury library budget.
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(es) where module will be delivered:
Canterbury
If the module is part of a programme in a Partner College or Validated Institution, please complete
the following:
20. Partner College/Validated Institution:
21. University School responsible for the programme:
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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"
................................................................
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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
SECTION 3: MODULE IS PART OF A PROGRAMME IN A PARTNER COLLEGE OR VALIDATED
INSTITUTION
(Where the module is proposed by a Partner College/Validated Institution)
Statement by the Nominated Officer of the College/Validated Institution (delete as applicable): "I
confirm that the College/Validated Institution (delete as applicable) has approved the introduction of the
module and will be responsible for its resourcing"
.................................................................
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Nominated Responsible Officer of Partner
College/Validated Institution
Date
………………………………………………….
Print Name
…………………………………………………..
Post
………………………………………….
Partner College/Validated Institution
Module Specification Template
Last updated February 2013
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