Four Critical Steps in Building Linear Regression Models
Instructor: Jeff Meyer
Take the frustration out of linear regression model building.

A primary consideration in model building is which variables to include in the model. A secondary one is deciding which predictors to retain in the model.

But the decisions don’t stop there. A number of other considerations can make model building either very straightforward or extremely frustrating.

While you’re worrying about entering predictors, you might be missing topics that have a big impact your analysis. 

In this one hour presentation, Jeff tackles four topics that you need to consider when building a regression model. They will give you more accurate results and a less-frustrating model building experience.

Covered in this webinar:

The value of graphs and tables before you begin
When and how to add interactions
Using segmented regression for discontinuous relationships
Graphing residuals to check for normality and constant variance