Module 7: Regression and binary and categorical outcomes

Prerequisites

Module is designed to teach students how to analyse different types of data using SPSS; including outputs, conducting diagnostic tests, calculating effect sizes and make predictions.

Mphil Students from participating departments taking the Social Science Research Methods Course as part of their research degree

Students expected to be familiar with the basic logic of statistical reasoning and concepts of variance and correlation.

Number of sessions: 4

• Session 1: Introduction & Binary I Probability,odds & logit
• Session 2: Binary II: Logistic regression in SPSS
• Session 3: Binary III Diagnostics for logistic regression
• Session 4: Binary IV, categorical and ordinal.

• The objective is to teach students how to analyse different types of data using SPSS

To enable students to deal with outcomes that form "yes" or "no" responses to questions and unordered or ordered response variable

Presentations, demonstrations and practicals

SPSS v. 16 on PWF Windows

Three exercises

• Field,A. Discovering Statistics Using SPSS. London:Sage.
• Tarling, R (2009) Statistical Modelling for Social Researchers: Principles and Practice. London: Routledge.

• Students also expected to have read: http://www.statsoft.com/textbook/stathome.html Chapter on 'Nonlinear estimation'

• To gain the maximum benefits from the course it is important that students do not see this course in isolation from the other MPhil courses or research training they are taking. Responsibility lies with each student to consider the potential for their own research using methods common in fields of the social sciences that may seem remote. Ideally this task will be facilitated by integration of the SSRMC with discipline-specific courses in their departments and through reading and discussion.

Four sessions of two hours

Four times in Michaelmas term

• Advanced Statistics
• JISC Digital Proficiency