This activity can stand alone and also is a companion activity to the Mastering JMP session Disentangling and Organizing Wide Data.
This hands-on activity allows you to practice using Explore Missing Values to understand patterns in missing values across predictor variables in a predictive modeling exercise.
The instructions are below and in the attached PDF, which also contains the solutions. The Product Quality JMP data table is also attached to this post.
The data are in the Product Quality data table. They represent two response variables (Y1 and Y2) and nineteen predictor variables (X1 through X19) measured on 568 runs of a manufacturing process.
Answer the following questions:
- Are there any missing response values?
- How many predictor variables have at least one missing observation?
- Are there patterns to the missing observations?
Interested in a related activity on managing yourdata? See Explore Outliers Hands-on Practice and Solution.