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.

1.

The value of graphs and tables before you begin

2.

When and how to add interactions

3.

Using segmented regression for discontinuous relationships

4.

Graphing residuals to check for normality and constant variance