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Introduction to Robust Estimation and Hypothesis Testing (Statistical Modeling and Decision Science) 1st Edition

2 customer reviews
ISBN-13: 978-0127515458
ISBN-10: 0127515453
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Editorial Reviews

Review

"The two biggest strengths of Introduction to Robust Estimation and Hypothesis Testing, by Rand R. Wilcox, are its practical usability and its inherent structure....Introduction to Robust Estimation and Hypothesis Testing is a nice complement to other books in the area of robust methods."
--Paul S. Horn, University of Cincinnati, TECHNOMETRICS

About the Author

Rand R. Wilcox has a Ph.D. in psychometrics, is a professor of psychology at the University of Southern California, and a Fellow of the Royal Statistics Society and American Psychological Society. He is an internationally recognized expert in the field of Applied Statistics and has concentrated much of his research in the area of ANOVA and Regression. He has authored twobooks and more than 130 journal articles.

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Product Details

  • Series: Statistical Modeling and Decision Science
  • Hardcover: 296 pages
  • Publisher: Academic Press; 1st edition (April 7, 1997)
  • Language: English
  • ISBN-10: 0127515453
  • ISBN-13: 978-0127515458
  • Product Dimensions: 0.8 x 6.5 x 9.5 inches
  • Shipping Weight: 1.4 pounds
  • Average Customer Review: 3.0 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon Best Sellers Rank: #4,768,266 in Books (See Top 100 in Books)

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34 of 42 people found the following review helpful By A Customer on October 30, 2000
Format: Hardcover
Dr. Wilcox apparently works copiously but unaccompanied (36 of the book's technical references attribute sole authorship to him). With all due respect to the author, lack of collaboration can be detrimental to what was intended to be a basic technical treatise - and this may be one of those occasions. The author notes (p. 11) "We stress, however, that many mathematical details arise that are not discussed here. The goal is to provide an indication of how technical issues are addressed without worrying about the many relevant details." Indeed, the reader may find this concentration of effort a bit contrary with the introductory nature implied by the book's title. This impression is reinforced by a subject index perhaps too terse for an introductory or reference textbook (being only 3 pages of regularly-sized font, while a less-useful "author index" takes up almost 4 pages).
For the most part, this lean 296 page book is not so much an "Introduction to Robust Estimation" as it is a tutorial or user's manual for numerous S-PLUS functions relevant to the subject matter. If the reader is not heavily invested in S-PLUS (S-PLUS being a high-level computer language and interactive analysis environment trademarked by MathSoft, Inc.), he can never fully appreciate the contents of this title. For example, in the discussion of median variance (p. 42), the author notes that this estimator is related to the beta distribution, but does not acknowledge that there are several related functions that can take this name (such as the incomplete beta distribution, as well as its ratio). Instead, an S-PLUS function 'pbeta' defines what was meant.
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7 of 9 people found the following review helpful By A Customer on January 6, 2001
Format: Hardcover
If you want a useful book on modern ANOVA and regression methods, this is an excellent choice. The book begins with some technical background on robust techniques and then focuses on how commonly encountered problems can be addressed. Included are two-way and three-way designs, split-plot designs, a variety of robust regression methods plus some recently developed exploratory tools. The book also contains a description of s-plus functions that can be used to implement the methods covered. The s-plus functions used can be downloaded for free. S-plus is easy to use and learn and I make use of these functions on a regular basis. If you are more interested in theory than applied work, other books, such as Staudte and Sheather, or Huber, or Hampel et al. will be more interesting. But for applied work, this is the only book I've read that covers many experimental designs that are typically encountered in practice. Even some modern advances related to least squares are covered and can make a substantial difference in accuracy as well as the conclusions reached.
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