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Identifying Important Variables in Your Data


See how to:

  • Find important factors in large data using Response Screening
    • Examine FDR PValue Plot, FDR LogWorth by Effect Size, FDR LogWorth by RSquare
  • Identify important variables using Predictor Screening, a decision-tree based method for screening many predictors for their ability to predict an outcome
  • Identify unique important variables using variable clustering to group similar variables into representative groups
    • Understand and examine how each cluster can be represented by a single component or variable to eliminate  multicollinearity between variables
    • Interpret Color Map on Correlations, Cluster summary, Cluster Members and Standard Components reports
  • Identify interactions among unique and important factors using Fit Model - Response Screening
    • Interpret FDR PValue Plot and FDR LogWorth by Rank Fraction reports using Graph Builder
  • Identify the best subset of variables and interactions for building Regression Models
    • Group similar variables into representative groups
    • Interpret Stepwise Regression Control and Estimates reports

NOTE: Q&A is included at times 18:23, 19:12, 34:07, 42:14, 43:50, 45:07, 46:06, and 47:23.


Steps in Identifying Important Variables.JPG


Attached JMP Journal should work for all.  Project file .zip file includes a JMP 15 Project Archive that requires unzipping to work with JMP 15 or later.  See JMP archive documentation for help after you unzip the file.


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Use Videos and Resources to Practice JMP, JMP Pro, JMP Clinical and JMP Genomics.

1-hour live Mastering JMP webinars occur most Fridays from January through October. After each session, we hope you will use the video and resources shared by the presenting JMP Systems Engineers to practice what you saw.

Mastering JMP Videos are available here.