This market leading text provides experimental scientists in a wide variety of disciplines with a readable introduction to the statistical analysis of multivariate observations. It's overarching goal is to provide readers with the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. The Fourth Edition has been revised to take greater advantage of graphical displays of multivariate data and of statistical software programs that facilitate the analysis of complex data.
- The applications of multivariate methods are emphasized. The mathematics is made as accessible as possible. Matrices are introduced as they appear naturally in the discussion and the authors teach how to simplify the presentation of multivariate models and techniques.
- Chapter 2 provides a summary of matrix algebra results for those with little or no previous exposure to the subject. This supplementary material helps make the book more self-contained and is used to complete proofs for those desiring greater depth.
- The methodological "tools" of multivariate analysis are contained in chapters 5-12. These chapters represent the heart of the book but are divided into three units to allow instructors some flexibility in tailoring a course to their needs. Chapters 1-4 provide the requisite background and may be taught or assigned as review depending on the background of individual students.
- NEW - Graphical displays of multivariate data moved from Chapter 12 to chapter 1 and many new illustrations and graphics have been added to provide a more visual approach to the subject.
- NEW - discussions of important topics including:
- Detecting Outliners and Data Cleaning in Chapter 4.
- Multivariate Quality Control in Chapter 5.
- Monitoring Quality with Principal Components in Chapter 8.
- Correspondence Analysis, Biplots, and Procrustes Analysis in Chapter 12.
- NEW - EXPANDED coverage of the following topics: Generalized variance, Assessing normality and transformations to normality, Repeated measures designs, Model checking and other aspects of regression, and Cluster analysis.
- NEW - The exercise sets have been updated and many new problems have been added.
- NEW - More extensive use of statistical software programs is now present in the book with an emphasis on interpretation of output. Many new data sets are available on the Data Disk in the back of the book.