Module Directory

This module is focused on statistical models and begins with simple OLS regression and provides a framework for modelling strategy and variable selection. Students are then taken through extensions to the basic OLS model, with categorical predictors, interactions and non-linear terms. Next, we introduce models for categorical outcomes, binary and multinomial logistic regression. The final part of the term deals with concepts and models of measurement, along with basic techniques for implementing them using multi-item summated scales and factor analysis. The modelling framework outlined in this term gives students a springboard for builds the foundations for advanced quantitative social science methods.

The aims of this module are:

• To develop students’ understanding of quantitative methods in general and how to build statistical models representing sociological and criminological processes and behaviours.


• To teach students the practical skills necessary for carrying out advanced statistical analysis of sociological and criminological data using modern statistical software and programming.

By the end of this module, students will be expected to be able to:

1. understand the principles and practice of statistical modelling


2. critically evaluate research articles that use statistics


3. understand the link between substantive theory, measurement and statistical models


4. carry out intermediate and advanced statistical analysis using SPSS and other software

Topic 1 - week 2 - Introduction to the course. Aims and Objectives.

Topic 2 - week 3 - Review: OLS linear regression

Topic 3 - week 4 - Interpreting statistical models: Lazarsfeld’s method of elaboration

Topic 4 - week 5 - Extensions to the multiple linear  regression model: dummy variables and interactions

Topic 5 - week 6 - Continuous interactions and nonlinear effects (quadratic/polynomials)

Topic 6 - week 7 - The generalised linear model; categorical dependent variables: the binary logistic regression model

Topic 7 - week 8 - Multinomial logistic models

Topic 8 - week 9 - Criminological and social measurement: creating multi-item scales

Topic 9 – week 10 - Criminological and social measurement: factor analysis and latent variables

Topic 10 – week 11 - Assignment presentations

If you wish to take this module but have not taken the second year module 'Analysing Social Life' (SC202-5-AU), please contact the Module Convenor to see if you have the appropriate background in statistics. Please click on the link below to view the Introduction video to SC385 Models and Measurement in Quantitative Sociology https://moodle.essex.ac.uk/mod/page/view.php?id=668576

The teaching consists of online and face to face lectures, a weekly discussion class where students read and comment on a paper on a criminological or sociological case study that uses quantitative methods, and a computer lab session where students will learn how to build statistical models and analyse the results, using social and criminological real-world datasets.

Most modules in Sociology are divided into lectures of around 50 minutes and a class of around 50 minutes. Some are taught as a 2hr seminar, and others via a 50-minute lecture and 2-hr lab. Lectures, classes, labs and seminars will be taught face-to-face. Please note that you should be spending up to eight hours per week undertaking your own private study (reading, preparing for classes or assignments, etc.) on each of your modules (e.g. 32 hours in total for four 30-credit modules). The lectures provide an overview of the substantive debates around the topic of the week, while the classes will give you the opportunity to reflect on your learning and actively engage with your peers to develop your understanding further. You are strongly encouraged to attend the classes as they provide an opportunity to talk with your class teacher and other students. The classes will be captured and available via Listen Again. However, if you want to gain the most you can from these classes it is very important that you attend and engage. Please note that the recording of classes is at the discretion of the teacher.