Quantitative Research Methods
Structure:
The Quantitative Methods core training module will be offered in two full-time and one part-time versions. The Term 1 full-time version will be coordinated by Kevin Mole in the Warwick Business School is likely to be taught to all first-year PhD students from the Business School. However, it should be able to accommodate some students from other DTC departments. The term 2 full-time version will be coordinated by Richard Lampard in Sociology and is designed for students from across the DTC. The part-time version is one provided by the Institute of Education for its own research students, but will be available for part-time students from other departments.
Description:
Full-Time Term 1 (Kevin Mole)
Full-Time Term 2 (Richard Lampard)
The module will focus on concepts, methods and skills which are central to quantitative social research. In addition to quantitative data analysis, approaches to data collection and concept operationalisation will be considered. Key aspects of descriptive and inferential statistics will be covered, stretching from comparisons of means and the examination of simple cross-tabulations to an initial discussion of multivariate approaches focusing on regression. The illustration and application of the techniques will utilise statistical software, specifically SPSS for Windows, and will be based on 'hands-on' manipulation and analysis of data from existing, high profile quantitative sources.
Part-Time Option Offered by WIE (Steve Strand):
*NB: This option is intended for WIE students.
The module will address conceptual issues and advanced methods of quantitative data collection and analysis, grounded in practical examples and the study of 'real' research data. Methodological isues and statistical techniques will be introduced using the statistical package SPSS to give hands-on experience of putting analyses into practice. While the module deals with quantitative data, there is also consideration of the methodological issues around mixed-methods/combined methods approaches.