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DRPS : Course Catalogue : School of Social and Political Science : Postgrad (School of Social and Political Studies)

Postgraduate Course: Core quantitative data analysis for social research: part 2 (PGSP11079)

Course Outline
SchoolSchool of Social and Political Science CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThe course builds on the key statistical ideas and methods for social and political research learned in part 1 (PGSP11078) or through equivalent prior learning. It explores principles of inference and the logic of obtaining empirical evidence about populations from samples; confidence intervals; hypothesis formulation and testing; elementary multivariate analysis; and linear and logistic regression. The emphasis is on learning and understanding by doing, using 'real' data, rather than memorising formulae or rules of procedure. Each online learning module is supplemented by self-tests and activities to give students practice in the exploration and analysis of quantitative data using the SPSS software package, copies of which may also be provided free of charge to students for use on their own personal computers. In line with ESRC postgraduate research training guidelines, the aim of the course is to ensure that students are able to understand and use basic quantitative methods.
Course description This is a practical course in which students will learn the basics of conducting their own quantitative research using the SPSS statistical software package. It assumes a basic knowledge of statistical thinking and concentrates on issues of hypothesis testing and multivariate analysis, notably through the use of multiple and logistic regression.

Lectures are provided throughout the course in order to provide students with key information about the different statistical techniques covered by the course. However, the focus of teaching will be on 'learning through doing'. Online teaching materials are provided for each topic, allowing students to study at their own pace and to access detail of the different statistical techniques at a level with which they feel comfortable. These online materials are interactive, providing illustrations of the key research design issues involved in conducting quantitative research. They provide worked examples of the statistical techniques taught on the course, step-by-step examples of how to conduct your own analysis in SPSS and guidance as to how to interpret the results provided by the analysis.

In addition to the online materials and lectures, students attend a weekly microlab session in which they complete guided practicals to learn the use of the SPSS software package. These small group sessions, led by experienced quantitative researchers, provide a setting in which students can ask for further in depth advice on any techniques, or topics, they feel they do not fully understand.

The material covered on the course will help students develop a critical understanding of the pitfalls and strengths associated with the use of regression analysis in the social sciences.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Students MUST NOT also be taking Core quantitative data analysis for social research: part 1 (PGSP11078)
Other requirements A pass in part 1 (PGSP11078) or equivalent prior learning
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Not being delivered
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand the links between theory and method, including the potential and limitations of quantitative evidence
  2. Understand the theoretical basis for making inferences about populations from samples
  3. Understand how to use computer software for inferential statistical analysis of large datasets
  4. Understand and apply simple and multivariate regression analyses with continuous and discrete data
  5. Communicate statistical evidence through graphs, tables and text
Reading List
Elliot J. and Marsh C. (2008) Exploring Data (2nd edition), Cambridge: Polity.
Fielding J. and Gilbert N. (2006) Understanding Social Statistics (2nd edition), London: Sage.
Additional Information
Graduate Attributes and Skills Not entered
KeywordsNot entered
Course organiserDr Paul Norris
Tel: (0131 6)50 3922
Course secretaryMrs Beth Richardson-Mills
Tel: (0131 6)51 1659
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