The University of Southampton
Courses

RESM6007 Quantitative Methods II

Module Overview

Quantitative Methods II builds upon the material learnt in Quantitative Methods I and introduces students to some commonly used statistical methods for analysing data.

Aims and Objectives

Module Aims

The aim is to introduce you to some commonly used statistical methods for analysing data involving two or more variables per observation. More specifically, the module covers logistic regression and other models for categorical data, and shortly introduces data reduction methods such as principal component analysis and factor analysis. The module aims to provide a firm understanding of the use of these methods for the analysis of quantitative data and their application in a range of disciplinary contexts. The emphasis will be on the practical application of these statistical techniques to quantitative data using the statistical software SPSS and then interpreting and presenting the results.

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Demonstrate knowledge and understanding of core methods of regression modelling.
  • Select appropriate statistical methods in order to answer specific research questions.
  • Analyse quantitative data using SPSS.
  • Conduct, interpret and report statistical analyses. Critically evaluate the results of such analyses.

Syllabus

The course covers logistic regression and other models for categorical data. Indicative topics include: binary response variables, the linear probability model, probabilities and odds, the logistic regression model, model interpretation, model selection, multinomial logistic regression, models for ordinal data, and log-linear models. The final part of the module covers a short introduction to the data reduction methods of principal component analysis and factor analysis.

Learning and Teaching

Teaching and learning methods

Teaching will be through a combination of lectures, tutorials and computer workshops. Learning activities will include learning in lectures, which will cover explanations of the statistical techniques and their use, discussing problems during the tutorials, as well as by independent study. The computer workshops will provide hands-on experience of the analysis of data and the application of the techniques introduced in the lectures using SPSS

TypeHours
Independent Study80
Teaching20
Total study time100

Resources & Reading list

Software requirements. You will require access to SPSS, which is available on the University’s computer workstations and can be downloaded to your own computer for use with your studies.

Hosmer, D. W. and Lemeshow, S. (2000). Applied Logistic Regression. 

Agresti, A. (2007). An Introduction to Categorical Data Analysis. 

Manly, B. F. J. (2005). Multivariate Statistical Methods: a Primer. 

Field, A. (2009). Discovering Statistics Using SPSS. 

Assessment

Summative

MethodPercentage contribution
Coursework assignment(s)  (3000 words) 100%

Referral

MethodPercentage contribution
Coursework assignment(s)  (3000 words) 100%

Repeat Information

Repeat type: Internal & External

Linked modules

Pre-requisites: RESM6004

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