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Tue 12 Oct, Tue 19 Oct, ... Tue 2 Nov 2010
16:00 - 18:00

Venue: Titan Teaching Room 2

Provided by: Joint Schools' Social Sciences


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Module 5: Further Regression Topics
Prerequisites

Tue 12 Oct, Tue 19 Oct, ... Tue 2 Nov 2010

Description

This module is concerned with greater knowledge of regression, through extension of the simple linear model; enabling students to assess the models they use, testing for problems such as collinearity, outliers/leverage, and heteroskdasticity.

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 basic logic of statistical reasoning and linear regression up to the JSSS standard.

Sessions

Number of sessions: 4

# Date Time Venue Trainer
1 Tue 12 Oct 2010   16:00 - 18:00 16:00 - 18:00 Titan Teaching Room 2 A. Sutherland
2 Tue 19 Oct 2010   16:00 - 18:00 16:00 - 18:00 Titan Teaching Room 2 A. Sutherland
3 Tue 26 Oct 2010   16:00 - 18:00 16:00 - 18:00 Titan Teaching Room 2 A. Sutherland
4 Tue 2 Nov 2010   16:00 - 18:00 16:00 - 18:00 Titan Teaching Room 2 A. Sutherland
Topics covered
  • Session 1: Recap on simple & multiple regression
  • Session 2: The importance of diagnostics I Checking model assumptions
  • Session 3: The importance of diagnostics II Outliers, influential cases and residuals
  • Session 4: Non-linearity & interaction effects
Objectives
  • The objective is to enable students to access the models they use
  • To test for problems ie collinearity; outliers/leverage and heteroskedasticity
Aims
  • To understand non-linear effects; variable transformations
  • to think about how statistical models are built
  • to introduce interaction effects
Format

Presentations, demonstrations and practicals

Taught using

SPSS v. 16 on PWF Windows

Assessement

Three exercises

Textbook(s)
  • Field, Andy (2009), Discovering Statistics using SPSS. London:Sage
  • Jaccard, J.and Turrisi, R. (2003) Interaction Effects in Multiple Regression (2nd ed.) London:Sage
  • Student also expected to read Linear Regression chapter on EST: http://www.statsoft.com/textbook/sstathome/html
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
Duration

Four sessions of two hours

Frequency

Four times in Michaelmas term

Theme
Advanced Statistics

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