SAS Training
SAS Programming
Statistical Consulting
Arthur L. Carpenter


Principles of Regression Analysis  

1       Simple Linear Regression
2       Multiple Linear Regression
3       Model Selection
4       Examining the Data and Model Assumptions
5       The Constant Variance and Normality Assumptions
6       Multicollinearity
7       Biased Regression Techniques
8       Using the REG Procedure Interactively
9       Special Topics

This course is designed for students with a working knowledge of the SAS System and a basic understanding of statistical principles.

After completion of this course the student will be able to:

  • Perform an Ordinary Least Squares regression and analyze the results
  • Fit a multiple linear regression equation to data and discuss the outcomes
  • Understand various statistics generated by the SAS regression procedures
  • Evaluate the appropriateness of a model relative to the assumptions.
  • Discuss the concepts used with biased regression techniques