Empirical Issues in Multivariate Data Analysis: with readings
"synopsis" may belong to another edition of this title.
From the Publisher:
Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis greatly reduces the amount of statistical notation and terminology used while focusing instead on the fundamental concepts that affect the use of specific techniques. The fourth edition of this trusted text features an innovative and widely applicable six-step framework for each chapter, and the traditionally strong complement of revisited examples used throughout.
From the Back Cover:
Key Benefit: Well-suited for the non-statistician, this applications- oriented introduction to multivariate analysis greatly reduces the amount of statistical notation and terminology used while focusing instead on the fundamental concepts that affect the use of specific techniques. Features an innovative and widely applicable six-step framework for each chapter, and the traditionally strong complement of revisited examples used throughout. Key Topics: Includes detailed guidelines on approaches for interpretation of results. Contains readings in each chapter which emphasize the applications of the techniques. Presents step-by-step flowcharts for each technique, illustrating major issues in each and offering a clear graphical portrayal of the decision process used in applying each technique. Includes a new chapter encompassing the issues of handling missing data, testing and resolving statistical assumption issues, and outlier detection. Revised material on factor, MANOVA, multiple analysis regression and canonical correlation.
"About this title" may belong to another edition of this title.
- PublisherPearson College Div
- Publication date1995
- ISBN 10 0023490209
- ISBN 13 9780023490200
- BindingHardcover
- Number of pages745
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