Skip to main content

Unit information: Further Quantitative Methods in 2015/16

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Further Quantitative Methods
Unit code SPOLD0001
Credit points 20
Level of study D/8
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Turner
Open unit status Not open

SPOLD2031 Participants should usually have already taken the unit ‘Introduction to Quantitative Research Methods in the Social Sciences’ (SPOLM0015), or be able to demonstrate equivalent expertise.



School/department School for Policy Studies
Faculty Faculty of Social Sciences and Law

Description including Unit Aims

This unit builds upon the earlier module, Introduction to Quantitative Methods (SPOLD2031), by focusing upon techniques for the analysis of quantitative data. The unit covers three main topics:

  • The practice of secondary data analysis using survey sources based upon a range of statistical methods and ‘hands-on’ exercises using SPSS
  • The circumstances in which particular techniques can be applied, including an appreciation of the statistical problems and issues to be aware of in evaluating quantitative research designs
  • The strengths and weaknesses of different methods in informing policy and practice, including an awareness of the limitations of statistical inference
  • The interpretation of quantitative data and the dissemination of results in accessible ways which can inform policy and practice

Intended Learning Outcomes

Upon completion of this unit student should be able to:

  • Use descriptive methods in order to explore the properties of their data
  • Select an appropriate strategy of analysis for different types of quantitative data and in a variety of different research settings
  • Analyse the relationship between variables using a range of parametric and non-parametric approaches
  • Compare groups of cases using both parametric and non-parametric tests
  • Demonstrate a critical awareness of the strengths and limitations of statistical evidence in informing policy and practice
  • Apply principles for the effective dissemination of quantitative evidence to policy and practitioner audiences using appropriate data visualisation methods

Teaching Information

Lecture and demonstration. Many of the classes in this module involve an emphasis upon developing computer-based statistical analysis skills and will therefore be lab-based. These sessions will involve on-line classroom-based exercises designed to develop competency in using SPSS for the analysis of quantitative data.

Assessment Information

Summative assessment will be by means of a written assignment of not more than 4,000 words. Participants will be asked to apply the knowledge and skills they have developed during the course of the unit to the investigation of a key social policy problem based upon the secondary analysis of a large scale teaching data set.

Formative assessment will be primarily by means of student presentations delivered as part of the teaching program. Students will be asked to work in small groups to develop a research design in order to investigate a key social policy problem (e.g. ill health, crime, poverty) based upon exploration of a selected UK Data Archive teaching data set. Students will be asked to present their proposed research and will have an opportunity to receive feedback on this during the session.

Formative self-assessment by means of multiple choice questionnaires is also available to participants via the package “Statistics for the Terrified”. This will enable participants to better evaluate their progress, and to identify areas for revision or further development.

Many of the unit sessions are based upon lab-based activities involving analysis of large-scale datasets using the SPSS package. Students are asked to complete these tasks and write up their results in the associated workbooks which we review with students at the end of each session.

Reading and References

  • Bryman, A. and Cramer, D. (1996). Quantitative Analysis with SPSS for Windows: A guide for social scientists. London: Routledge.
  • Dorling, D. and Simpson, S. (Eds.) (1999). Statistics in Society: The arithmetic of politics. London: Arnold.
  • Field, A. (2009). Discovering Statistics Using SPSS. (3rd Ed.) London: Sage.
  • Levitas, R. & Guy, W. (1996). (Eds.) Interpreting Official Statistics. Routledge: London.
  • Marsh, C (1988). Exploring Data. Cambridge, Polity Press.
  • Tufte, E. (1990). Envisioning Information. Connecticut, Graphics Press.