Coronavirus (Covid-19): Latest updates and information
Skip to main content Skip to navigation

Multivariate Secondary Analysis of Social Data

Are you interested in developing the practical skills and technical understanding needed to carry out the kinds of analyses of social survey data that feature in published academic work? Or are you perhaps keen to be able to understand how researchers doing statistical analyses reached their conclusions? This module builds upon the foundations provided by the Year 2 module Practice and Interpretation of Quantitative Research, giving you an opportunity to extend and apply your research skills, and to develop your abilities as a research practitioner and also as a critic of the research of others.

This module moves you forward from a starting point of being able to identify relationships using statistical tests to a point where you can explain relationships using other measures, or see how relationships vary between different groups. So can differences between the educational achievements of children from different family types be understood, in relation to the differing material resources of such households? And do the educational achievements of children from different family types vary according to gender?

Multivariate techniques are forms of statistical analysis, involving three or more measures simultaneously, that allow such questions to be answered. They have been used in many important sociological studies, such as the classic studies of social class mobility in Britain. More advanced techniques allow you to look at things like outcomes that occur after varying periods of time, (or not at all), such as divorce, but still taking into account different explanations, such as how old someone was when they got married and whether they had lived with anyone else in the past.

We'll examine published articles, to see how authors have used statistical techniques, and to assess whether they have done so appropriately. Not all published quantitative research is free from errors and limitations! But most importantly, you'll have the opportunity to use powerful, (but user-friendly), statistical software to analyse real data from important social surveys, both during the module’s sessions and also when undertaking the data analysis project that forms the module assessment.

What do current students find most interesting about this module?

What students find compelling in this module is not so much the specific topics, but the way in which having access to data from large social surveys and being able to apply various statistical tools to them, allows a quantitative social researcher to answer interesting and important sociological questions.

Module Director:

Richard Lampard