University of Calgary

STAT 429 - Applied Regression Analysis - Fall 2011

Multiple linear regression model including parameter estimation, simultaneous confidence intervals and general linear hypothesis testing using matrix algebra. Applications to forecasting. Residual analysis and outliers. Model selection: best regression, stepwise regression algorithms. Transformation of variables and non-linear regression. Computer analysis of practical real world data.
This course may not be repeated for credit.

Hours

  • H(3-1T)

Notes

  • Statistics 421 is highly recommended as preparation

Prerequisite(s)

  • Statistics 323 or Mathematics 323 and Mathematics 353.
Syllabus

Sections

  • LEC 1TR 15:30 - 16:45
    BlackboardOutline
    TUT 1W 16:00 - 16:50
    TUT 2R 10:00 - 10:50
This course will be offered next in Fall 2012.
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