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CATEGORICAL DATA ANALYSIS

Module code: MT466S
Credits: 5
Semester: 2
Department: MATHEMATICS AND STATISTICS
International:

	Overview
	Module Objective: To introduce the students to categorical data analysis. Comparison of proportions and odds. Two-way contingency tables: Chi-squared test, Fisher's exact test. Three-way contingency tables: partial association, Cochran-Mantel-Haenszel methods. Generalized linear models, exponential families. Logistic regression for binary responses and Binomial counts. Loglinear models for Poisson counts, two and three-way tables.

Overview

Module Objective:
To introduce the students to categorical data analysis.

Comparison of proportions and odds. Two-way contingency tables: Chi-squared test, Fisher's exact test. Three-way contingency tables: partial association, Cochran-Mantel-Haenszel methods. Generalized linear models, exponential families. Logistic regression for binary responses and Binomial counts. Loglinear models for Poisson counts, two and three-way tables.

	Learning Outcomes
	On successful completion of the module, students should be able to: Compute and evaluate measures of association between categorical variable. Make a comparison of proportions. Examine data using two and three way contingency tables. Fit and interpret generalized linear models.

Teaching & Learning methods

Assessment

	Autumn Supplementals/Resits
	Continuous assessment mark is carried forward to the Autumn. University scheduled written examination (Autumn): 90 minutes

	Pre-Requisites
	MT463S

	Timetable
	This timetable is not currently available, please contact the Mathematics And Statistics Department.