Level: Intermediate
Ruth Hummel, JMP Academic Ambassador, SAS
Mary Loveless, JMP Systems Engineer Manager, SAS
You have a business or research question, you’ve collected or found appropriate data, and you are ready to analyze. But which analytical methods should you try? And how will you choose a final model? In this talk, we will look at several data scenarios and present modeling options and a framework for comparison. We will look at how different questions or goals affect the modeling choices we make. (Predict? Explain? Find associations?) Models covered will include traditional regression, penalized regression, partial least squares and a few others. Comparison techniques will include residuals analysis, comparing fit statistics, and cross-validation or validation on new data.
