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ST 462

Advanced Regression Analysis

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This course provides a broad overview of modern statistical methods for regression analysis. Statistical methodology may include generalized linear models, generalized additive models, multilevel modelling, nonparametric methods and an introduction to survival analysis. Exclusions: MA348.

This course provides a broad overview of modern statistical methods for regression analysis. Statistical methodology may include generalized linear models, generalized additive models, multilevel modelling, nonparametric methods and an introduction to survival analysis. Exclusions: MA348.

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This course provides a broad overview of modern statistical methods for regression analysis. Statistical methodology may include generalized linear models, generalized additive models, multilevel modelling, nonparametric methods and an introduction to survival analysis. Exclusions: MA348.

ST 462 Prerequisites

ST 362 (Min. Grade D-)

ST 462 Leads To

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ST 462 Restrictions

Must be enrolled in one of the following Levels:

Undergraduate (UG)

ST 462

Advanced Regression Analysis

0%Liked

Easy

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Useful

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0 ratings

This course provides a broad overview of modern statistical methods for regression analysis. Statistical methodology may include generalized linear models, generalized additive models, multilevel modelling, nonparametric methods and an introduction to survival analysis. Exclusions: MA348.

This course provides a broad overview of modern statistical methods for regression analysis. Statistical methodology may include generalized linear models, generalized additive models, multilevel modelling, nonparametric methods and an introduction to survival analysis. Exclusions: MA348.

0%Liked

Easy

0%

Useful

0%

0 ratings

This course provides a broad overview of modern statistical methods for regression analysis. Statistical methodology may include generalized linear models, generalized additive models, multilevel modelling, nonparametric methods and an introduction to survival analysis. Exclusions: MA348.

Course Schedule