Book description
JMP 12 Multivariate Methods describes techniques for analyzing several variables simultaneously. The book covers descriptive measures, such as correlations. It also describes methods that give insight into the structure of the multivariate data, such as clustering, principal components, discriminant analysis, and partial least squares.
Table of contents
- Contents
-
Learn about JMP
- Documentation and Additional Resources
- Formatting Conventions
-
JMP Documentation
- JMP Documentation Library
- Discovering JMP
- Using JMP
- Basic Analysis
- Essential Graphing
- Profilers
- Design of Experiments Guide
- Fitting Linear Models
- Specialized Models
- Multivariate Methods
- Quality and Process Methods
- Reliability and Survival Methods
- Consumer Research
- Scripting Guide
- JSL Syntax Reference
- JMP Help
- Additional Resources for Learning JMP
- Introduction to Multivariate Analysis
-
Correlations and Multivariate Techniques
- Explore the Multidimensional Behavior of Variables
- Launch the Multivariate Platform
- The Multivariate Report
- Multivariate Platform Options
- Example of Item Reliability
- Computations and Statistical Details
- Cluster Analysis
- Principal Components
- Discriminant Analysis
-
Partial Least Squares Models
- Develop Models Using Correlations between Ys and Xs
- Overview of the Partial Least Squares Platform
- Example of Partial Least Squares
- Launch the Partial Least Squares Platform
- Model Launch Control Panel
- Partial Least Squares Report
- Partial Least Squares Options
- Model Fit Options
- Statistical Details
- References
- Statistical Details
- Index
Product information
- Title: JMP 12 Multivariate Methods
- Author(s):
- Release date: March 2015
- Publisher(s): SAS Institute
- ISBN: 9781629594606
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