Minitab Cookbook

Chapter 9. Multivariate Statistics

In this chapter, we will cover the following recipes:

• Finding the principal components of a set of data
• Using factor analysis to identify the underlying factors
• Analyzing the consistency of a test paper using item analysis
• Finding similarity in results by rows using cluster observations
• Finding similarity across columns using cluster variables
• Identifying groups in data using cluster K-means
• The discriminant analysis
• Analyzing two-way contingency tables with a simple correspondence analysis
• Studying complex contingency tables with a multiple correspondence analysis

Introduction

Multivariate tools can be useful in exploring large datasets. They help us find patterns and correlations in the data; or, try to identify groups ...