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Mathematical Statistics
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Mathematical Statistics

Book Details

Format Hardback or Cased Book
ISBN-10 158488178X
ISBN-13 9781584881780
Publisher Taylor & Francis Inc
Imprint Chapman & Hall/CRC
Country of Manufacture GB
Country of Publication GB
Publication Date Nov 24th, 1999
Print length 498 Pages
Weight 876 grams
Dimensions 16.20 x 24.00 x 3.50 cms
Product Classification: Probability & statistics
Ksh 30,600.00
Werezi Extended Catalogue 0 in stock

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Presents a set of useful tools that allow readers to understand the theoretical underpinnings of statistical methodology. This title emphasizes inferential procedures within the framework of parametric models.

Traditional texts in mathematical statistics can seem - to some readers-heavily weighted with optimality theory of the various flavors developed in the 1940s and50s, and not particularly relevant to statistical practice. Mathematical Statistics stands apart from these treatments. While mathematically rigorous, its focus is on providing a set of useful tools that allow students to understand the theoretical underpinnings of statistical methodology.

The author concentrates on inferential procedures within the framework of parametric models, but - acknowledging that models are often incorrectly specified - he also views estimation from a non-parametric perspective. Overall, Mathematical Statistics places greater emphasis on frequentist methodology than on Bayesian, but claims no particular superiority for that approach. It does emphasize, however, the utility of statistical and mathematical software packages, and includes several sections addressing computational issues.

The result reaches beyond "nice" mathematics to provide a balanced, practical text that brings life and relevance to a subject so often perceived as irrelevant and dry.

Features

  • Provides the tools that allow an understanding of the underpinnings of statistical methods
  • Encourages the use of statistical software, which widens the range of problems reader can consider
  • Brings relevance to the subject-shows readers it has much to offer beyond optimality theory
  • Focuses on inferential procedures within the framework of parametric models, but also views estimation from the nonparametric perspective
  • Solutions manual availalbe on crcpress.com
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