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STAT429

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Linear Models and Their Applications

Mathematics and StatisticsSC - Faculty of Science
Overview

Subject

STAT - Statistics

Description

Multiple linear regression model, parameter estimation, simultaneous confidence intervals and general linear hypothesis testing. Residual analysis and outliers. Model selection: best regression, stepwise regression algorithms. Transformation of variables and non-linear regression. Applications to forecasting. Variable selection in high-dimensional data using linear regression. Computer analysis of practical real world data.

Prerequisite(s): Statistics 323 or Data Science 305; and Mathematics 211.

GFC Hours

(3-1T)

Domestic Fee Rate Group

A

International Fee Rate Group

A

Signature Learning

Research & Creative Scholarship

Courses may consist of a Lecture, Lab, Tutorial, and/or Seminar. Students will be required to register in each component that is required for the course as indicated in the schedule of classes. Practicums, internships or other experiential learning modalities are typically indicated as a Lab component.

Component

LEC

Component

TUT

Units

3

Repeat for Credit

No
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