This JMP - Finding Important Predictors training course teaches techniques for fitting statistical models to identify important variables. Manual, graphical, and automated variable selection techniques are presented, along with advanced modeling methods. The demonstrations include modeling both designed and undesigned data. Techniques are illustrated using both JMP software and JMP Pro software.
By attending JMP - Finding Important Predictors workshop, delegates will learn to:
- Identify a subset of predictors as important using a statistical model
- Vvalidate statistical models using cross-validation, holdback validation, and information-theoretic criteria
- Perform stepwise and all subsets regression
- Select important predictors using decision trees, variable clustering, and predictive models
- Perform penalized regression for gaussian and non-gaussian responses
- Use the generalized regression platform to identify important predictors.
- Experience using JMP and performing data analysis.
The JMP - Finding Important Predictors class is ideal for:
- Analysts, researchers, technicians, or anyone filling similar roles, who want to determine which predictors in a large set are important in predicting a response