MRes Criminology (Social Statistics)

Year of entry: 2021

Coronavirus information for applicants and offer-holders

We understand that prospective students and offer-holders may have concerns about the ongoing coronavirus outbreak. The University is following the advice from Universities UK, Public Health England and the Foreign and Commonwealth Office.

Read our latest coronavirus information

Course unit details:
Introduction to Statistical Modelling

Unit code SOST70011
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 1
Offered by Social Statistics
Available as a free choice unit? Yes



1) Enable students to model data from large social surveys using linear and binary logistic regression modelling, and factor analysis.

2) Enable students to use such models to carry out hypothesis testing and to make valid inferences from the survey sample to the population of interest.

3) Enable students to interpret and critically evaluate the results of such modelling and inferential analyses.

4) Provide students with the skills to use SPSS to carry out the above analyses.

Teaching and learning methods

The course will be delivered in eleven 2-hour classes consisting either of a lecture or a Q&A session followed a hands-on practical exercise. In the exercise the students will be required to carry out formative tasks designed to strengthen their understanding. Weekly back-up support will also be provided in the form of office hours. The students will be required to complete three pieces of formative homework and they will receive feedback on that work. The homework will either be in the form of structured short-answer questions requiring students to run and interpret simple analyses, or in the form of short reports on existing analyses. The latter will enable students to practice and receive feedback on the skills required for the assessment.

Knowledge and understanding

  • To understand the principles of several regression modelling, data reduction and classification (DRC) techniques.
  • To understand the practical application of the statistical concept of variance.

Practical skills

  • To produce and interpret regression models and DRC analyses and the necessary supporting exploratory analyses in SPSS.
  • To decide on a plan of action for hypothesis testing of a research question, given large-scale social survey data.  To write coherent reports about a piece of quantitative data analysis.


Assessment methods

Essay of 3000 words worth 100%.

Recommended reading

Field, A. (2013). Discovering Statistics Using SPSS (2nd Ed.). London:  Sage Publications.

Linneman, T. (2011). Social Statistics: The basics and beyond. Taylor & Francis.

(Linneman covers regression in much more practical detail than Field, but does not cover factor analysis.)

Study hours

Scheduled activity hours
Lectures 22
Independent study hours
Independent study 128

Teaching staff

Staff member Role
Nicholas Shryane Unit coordinator

Additional notes

Compulsory for SRMS

Pre-Requisite for CSDA,  SEM and LDA


Thursday 2-4 Remote access to Simon 6.004 cluster

Return to course details