Name: Logistic Regression
Start: 2014-10-15
End: 2014-10-15
Location: Humanities Bridgeford Street, Oxford Road, Manchester

Logistic Regression

Date:

15/10/2014

Organised by:

University of Manchester

Presenter:

Dr Maria Pampaka (http://www.manchester.ac.uk/research/maria.pampaka/)

Level:

Entry (no or almost no prior knowledge)

Contact:

Short courses administrator; cmist-courses@manchester.ac.uk

Map:

View in Google Maps (M13 9PL)

Venue:

Humanities Bridgeford Street, Oxford Road, Manchester

Description:

Outline

This course examines the fitting of models to predict a binary response variable from a mixture of binary and interval explanatory variables.

The approach is illustrated using examples from a social science perspective, including cases where logistic regression models are used as a means of analysing tabular data where one of the dimensions of the table is a two-category outcome variable.

You will also learn how to fit a logistic regression model, and how to interpret the results.

Objectives

At the end of the course participants should be able to:

Understand the concepts of odds and odds ratios.
Generate odds for a given contingency tables.
Understand the basic theory behind binary logistic regression.
Run and interpret a logistic regression model.
Interpret Log Likelihoods to evaluate models.
Choose between different models.

Prerequisites

Participants should have

a basic familiarity with SPSS;
an understanding of basic data analytical techniques and concepts such as cross tabulations, graphing, variance, significance testing and correlation;
an understanding of linear regression would be helpful but not essential.

The course is designed for users of survey data with some experience of data analysis, who are comfortable using SPSS and who want to expand their understanding of more sophisticated techniques.

Logistic Regression

Description:

Outline

Objectives

Prerequisites

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