Statistics (STAT) Courses>Applied Regression Analysis

STAT353 - Applied Regression Analysis

Description

An outline of linear regression theory with applications; multiple linear regression, polynomial regression, model adequacy checking, variable transformation, variable selection, indicator variable, diagnostics for leverage and influential observations, multicollinearity problem, model selection, stepwise regression, prediction and inference

Units

1.5

Hours: lecture-lab-tutorial

3-0-0

Prerequisites

  • Complete all of the following
    • Complete 1 of:
      • STAT256 - Statistics for Life Sciences II (1.5)
      • STAT261 - Introduction to Probability and Statistics II (1.5)
    • Complete 1 of:
      • MATH110 - Matrix Algebra for Engineers (1.5)
      • MATH211 - Matrix Algebra I (1.5)
  • or permission of the department.

Course offered by

Department of Mathematics and Statistics

Course schedules

Summer timetable available: February 15. Fall and Spring timetables available: May 15.

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