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MATH 511 Analysis of Categorical Data (4 credits)

Offered by: Mathematics and Statistics (Faculty of Science)

Overview

Mathematics & Statistics (Sci) : Probability distributions for categorical data, Analysis of 2X2 contingency tables, Multiway contingency tables, The Logistic regression, Logistic regression for categorical predictors, Logit models for nominal and ordinal responses, Log-linear models and modelling ordinal associations in contingency tables, Unsupervised learning techniques for categorical data, Non Linear Principal component analysis, Applications of unsupervised learning techniques using R, Item Response Theory, Rasch model. Some topics may be included or excluded as the time permits.

Terms: This course is not scheduled for the 2024-2025 academic year.

Instructors: There are no professors associated with this course for the 2024-2025 academic year.

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