Models and Measurement in Quantitative Sociology
Undergraduate: Level 6
Thursday 07 October 2021
Friday 17 December 2021
08 October 2021
Requisites for this module
SC203 or GV200 or GV207 or SC208
The first term of the 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 logistic and multinomial logit. The term concludes with a discussion of practical topics in survey data analysis – how to deal with complex sample designs, weighting and non-response adjustments. The modelling framework outlined in this term builds the foundations for advanced quantitative social science methods.
Case studies from social sciences (e.g., decision making in criminal justice, censorship and collective action, social networks and public health) will be used throughout the course to provide synergy between sociological issues, statistical techniques, and data analysis. The students will engage with data-driven exercises, which they will consolidate in research portfolios demonstrating their data science accomplishments in the domain of sociology as well as employability skills.
This module will develop students' understanding of quantitative analysis and impart the practical skills necessary for carrying out advanced statistical analysis of social data using modern statistical software.
By the end of course students should be able to:
understand the principles and practice of statistical modelling
critically evaluate research articles that use statistics
understand the link between substantive theory, measurement and statistical models
carry out intermediate and advanced statistical analysis using SPSS and other software
If you wish to take this module but have not taken the second year module 'Researching Social Life II' (SC203-5-FY), please contact the module supervisor 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
As there are still restrictions related to COVID-19 in place, some of the teaching on most modules will take place online. 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. For the majority of modules the lecture-type content will be delivered online – either timetabled as a live online session or available on Moodle in the form of pre-recorded videos. You will be expected to watch this material and engage with any suggested activities before your class each week. Most classes labs and seminars will be taught face-to-face (assuming social distancing allows this).
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. The weekly classes will take place face-to-face (unless there is a change in the current COVID safety measures). 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.
- Field, Andy P. (2018) Discovering statistics using IBM SPSS statistics, London: SAGE.
- Field, Andy P. (2018) 'Correlation', in Discovering statistics using IBM SPSS statistics, London: SAGE.
The above list is indicative of the essential reading for the course. The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students. Further reading can be obtained from this module's reading list.
Assessment items, weightings and deadlines
|Coursework / exam
||Data Analysis Report
Module supervisor and teaching staff
Prof Nick Allum, email: firstname.lastname@example.org.
Professor Nick Allum
Jane Harper, Undergraduate Administrator, Telephone: 01206 873052
Dr Jennifer Fleetwood
Goldsmiths, University of London
Senior Lecturer in Criminology
Available via Moodle
Of 33 hours, 14 (42.4%) hours available to students:
19 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.
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