University of Calgary

STAT 429 - Linear Models and Their Applications - Fall 2021

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.
This course may not be repeated for credit.

Hours

  • H(3-1T)

Prerequisite(s)

  • Statistics 323 or Data Science 305; and Mathematics 211 or 213.

Sections

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