- Paperback: 740 pages
- Publisher: Pearson; 7 edition (17 July 2013)
- Language: English
- ISBN-10: 129202190X
- ISBN-13: 978-1292021904
- Product Dimensions: 21.7 x 27.6 cm
- Average Customer Review: 5.0 out of 5 stars See all reviews (2 customer reviews)
- Amazon Bestsellers Rank: 391,256 in Books (See Top 100 in Books)
- See Complete Table of Contents
Multivariate Data Analysis Paperback – 17 Jul 2013
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Top Customer Reviews
Most Helpful Customer Reviews on Amazon.com (beta) (May include reviews from Early Reviewer Rewards Program)
Unfortunately, the problem is the print quality is not good (some of the pages look like photo-copies, seriously), and the binding is horrible. Pages come out or were not glued to the spine to begin with.
I returned it because 6 pages were loose and fell out as I took the book out of the shipping box. Amazon sent a new replacement... and guess what? The second version was even worse, with 12 loose pages that came out of the binding. I'm returning the replacement for hopefully a good quality replacement. If the 3rd one is also poor quality, then I'll try the Kindle version out of desperation...
How can a book, which costs over $250, have loose pages?
According to the copyright info, the book was printed in America, by Pearson Prentice Hall publishing. Pearson used to produce quality products. I recommend avoiding this mess unless you really need it for a course. It's too expensive for such a shoddy product.
If you do buy it, I recommend you manually check each page to make sure they are properly glued to the binding. If not -- then replace it. Eventually, if enough people return this book, maybe Amazon will force the publisher to print quality editions. Good luck.
The analysis of multivariate data requires the extension of standard univariate statistical models and methods but also introduces new problems. Initial attention is given to Data Mining techniques such as summarising and displaying high dimensional data and to ways of reducing multivariate problems to more manageable univariate ones. This is followed by routine generalisations of standard distributions and statistical tests before consideration of new strategies for constructing hypothesis tests. Finally, problems specific to multivariate data such as discrimination and classification (use in medical diagnosis problems for example) are studied. Most of these methods can be implemented in standard computer packages.
This book shows that multivariate analysis are:
- Design for capability (also known as capability-based design)
- Inverse design, where any variable can be treated as an independent variable
- Analysis of Alternatives (A0A), the selection of concepts to fulfill a customer need
- Analysis of concepts with respect to changing scenarios
- Identification of critical design drivers and correlations across hierarchical levels.
Thank you to Joseph F. Hair, Ronald L. Tatham, Rolph E. Anderson, William Black for their excellent job..make my research so easy. Every Phd should have this book.
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