Preparing Data for Analysis with JMP

Chapter 11: Data Preparation for Analysis

Introduction

Common Issues and Appropriate Strategies

Distribution of Observations

Noisy Data

Skewness or Outliers

Scale Differences among Model Variables

Too Many Levels of a Categorical Variable

High Dimensionality: Abundance of Columns

Correlated or Redundant Variables

Missing or Sparse Observations across Columns

A PCA Example

Abundance of Rows

Partitioning into Training, Validation, and Test Sets

Aggregating Rows with Summary Tables

Oversampling Rare Events

Date and Time-Related Issues

Formatting Dates and Times

Some Date Functions: Extracting Parts

Aggregation

Row Functions Especially Useful in Time-Ordered Data

Elapsed Time and Date Arithmetic

Conclusion

References

Introduction

Once we have all ...