Ordinary least squares regression is a foundational statistical method in many academic research settings, but to draw meaningful conclusions from the results, you first should confirm that the regression model doesn’t exhibit any problems. If you’re in need of a primer on common problems in regression modeling and what to do if you encounter them, then this JMP Academic webinar is for you. Topics include:

• Creating composite variables to address correlation among predictors.
• Using weighted least squares to handle non-constant variance.
• Box-Cox transformations for stabilizing variance and handling skewed data.

Recorded using JMP Student Edition 19.

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