Introductory description

The aim of this module is to introduce students to the use of quantitative methods for sociologically relevant research. By the end of this module, students will be able to critically engage with published quantitative sociological research and undertake elementary quantitative data analysis independently. Students will be introduced to the use of statistical software for the analysis of large-scale quantitative data. We will build on research design skills acquired in other modules and we will aim to develop practical research skills related to quantitative methods. This module does not require any mathematical knowledge: we will aim to principally focus on substantive understanding of quantitative methods and how they fit within the wider discipline.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

1. Introduction to the Module
2. Descriptive Statistics / Measurement
3.  Bivariate Associations: The Chi-Square Test
4. Introduction to Correlation and Sampling/Representativeness 
5. Deciphering Multivariate Analysis I
6. Deciphering Multivariate Analysis II
7. Longitudinal and Life Course Research 
8. Selected Topics on Operationalization and Measurement
9. Contemporary Challenges in Social Survey Research

Learning outcomes

By the end of the module, students should be able to:

• Understand the principles of statistical inference
• Be able to conduct simple statistical analyses on existing large-scale datasets
• Have an understanding of the biases surrounding large-scale survey data
• Have familiarity with the basic functions of SPSS software including keeping syntax for data management purposes
• Have familiarity with simple linear regression and the use of multivariate statistical methods to answer sociological questions
• Think critically about the quality of published research in the field of quantitative sociology
• Appreciate the role of quantitative methods in substantive social science
• Confidently read published research using bivariate and multivariate quantitative methods;
• Plan the development of a quantitative project.

Indicative reading list

Agresti, A, Finlay, B (2014) Statistical Methods for the Social Sciences. Pearson Education: Essex,
UK.
Field, Andy (2013) Discovering statistics using IMB statistics: (and sex, and drugs, and rock n’roll)
Sage: London, UK
Gilbert, N (2008) Researching Social Life London: Sage
Schaeffer, N. C. & Presser, S. (2003). ‘The science of asking questions’. Annual Review of
Sociology, 29: 65-88.
Argyrous, G. (2011). Statistics for research: with a guide to SPSS. London: SAG

View reading list on Talis Aspire

Research element

This is a quantitative methods module. As such, it provides hands-on-experience on statistical analysis and consistently engages with issues surrounding data collection, data quality, and data interpretation.

Subject specific skills

knowledge and critical understanding of the well-established principles of the area(s) of study, and of the way in which those principles have developed
knowledge of the main methods of enquiry in the subject(s) relevant to the named award, and ability to evaluate critically the appropriateness of different approaches to solving problems in the field of study
an understanding of the limits of their knowledge, and how this influences analyses and interpretations based on that knowledge.
Typically, holders of the qualification will be able to:
use a range of established techniques to initiate and undertake critical analysis of information, and to propose solutions to problems arising from that analysis
undertake further training, develop existing skills and acquire new competences that will enable them to assume significant responsibility within organisations.

Transferable skills

ability to apply underlying concepts and principles outside the context in which they were first studied, including, where appropriate, the application of those principles in an employment context
effectively communicate information, arguments and analysis in a variety of forms
to specialist and non-specialist audiences and deploy key techniques of the discipline effectively
qualities and transferable skills necessary for employment requiring the exercise of personal responsibility and decision-making