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Instructor-led course

Provided by: Joint Schools' Social Sciences



2010


2011


2020



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Module 7: Regression and binary and categorical outcomes
Prerequisites


Description

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.

Target audience

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

Prerequisites

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

Topics covered
  • 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.
Objectives
  • The objective is to teach students how to analyse different types of data using SPSS
Aims

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

Format

Presentations, demonstrations and practicals

Taught using

SPSS v. 16 on PWF Windows

Assessement

Three exercises

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

Four sessions of two hours

Frequency

Four times in Michaelmas term

Themes

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