Real-world problems and data sets are the backbone of this groundbreaking book. Applied Multivariate Statistics with SAS® Software, Second Edition provides a unique approach to this topic, integrating statistical methods, data analysis, and applications. Now extensively revised, the book includes new information on
* mixed effects models
* applications of the MIXED procedure
* regression diagnostics with the correspoding IML procedure code
* covariance structures.
The authors' approach to the information aids professors, researchers, and students in a variety of disciplines and industries. Extensive SAS code and the corresponding output accompany sample problems, and clear explanations of the various SAS procedures are included. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both the theoretical and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression. In addition, a quick introduction to the IML procedure with special reference to multivariate data is available in an appendix. SAS programs and output integrated with the text make it easy to read and follow the examples. High-resolution graphs have been used in this new edition.
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Ravindra Khattree is an Indian-American statistician and professor of statistics at Oakland University. His contribution to the Fountain-Khattree-Peddada Theorem in Pitman measure of closeness is one of the important results of his work. Khattree is the coauthor of two books and has coedited two volumes. Dayanand N. Naik is the author of Applied Multivariate Statistics with SAS Software, 2nd Edition, published by Wiley.
Real-world problems and data sets are the backbone of this groundbreaking book. Applied Multivariate Statistics with SAS? Software, Second Edition provides a unique approach to this topic, integrating statistical methods, data analysis, and applications. Now extensively revised, the book includes new information on
* mixed effects models
* applications of the MIXED procedure
* regression diagnostics with the correspoding IML procedure code
* covariance structures.
The authors' approach to the information aids professors, researchers, and students in a variety of disciplines and industries. Extensive SAS code and the corresponding output accompany sample problems, and clear explanations of the various SAS procedures are included. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both the theoretical and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression. In addition, a quick introduction to the IML procedure with special reference to multivariate data is available in an appendix. SAS programs and output integrated with the text make it easy to read and follow the examples. High-resolution graphs have been used in this new edition.
Real-world problems and data sets are the backbone of this groundbreaking book. Applied Multivariate Statistics with SASÂ(R) Software, Second Edition provides a unique approach to this topic, integrating statistical methods, data analysis, and applications. Now extensively revised, the book includes new information on
* mixed effects models
* applications of the MIXED procedure
* regression diagnostics with the correspoding IML procedure code
* covariance structures.
The authors' approach to the information aids professors, researchers, and students in a variety of disciplines and industries. Extensive SAS code and the corresponding output accompany sample problems, and clear explanations of the various SAS procedures are included. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both the theoretical and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression. In addition, a quick introduction to the IML procedure with special reference to multivariate data is available in an appendix. SAS programs and output integrated with the text make it easy to read and follow the examples. High-resolution graphs have been used in this new edition.
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