9780138503635-013850363X-Mathematical Statistics: Basic Ideas and Selected Topics, Vol I (2nd Edition)

Mathematical Statistics: Basic Ideas and Selected Topics, Vol I (2nd Edition)

ISBN-13: 9780138503635
ISBN-10: 013850363X
Edition: 2nd
Author: Peter J. Bickel, Kjell A. Doksum
Publication date: 2000
Publisher: Pearson College Div
Format: Hardcover 556 pages
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Book details

ISBN-13: 9780138503635
ISBN-10: 013850363X
Edition: 2nd
Author: Peter J. Bickel, Kjell A. Doksum
Publication date: 2000
Publisher: Pearson College Div
Format: Hardcover 556 pages

Summary

Mathematical Statistics: Basic Ideas and Selected Topics, Vol I (2nd Edition) (ISBN-13: 9780138503635 and ISBN-10: 013850363X), written by authors Peter J. Bickel, Kjell A. Doksum, was published by Pearson College Div in 2000. With an overall rating of 3.7 stars, it's a notable title among other Applied (Mathematics) books. You can easily purchase or rent Mathematical Statistics: Basic Ideas and Selected Topics, Vol I (2nd Edition) (Hardcover) from BooksRun, along with many other new and used Applied books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.81.

Description

We now have an updated printing! Find more information at: http://vig.prenhall.com/catalog/academic/product/0,1144,0132306379,00.html. In response to feedback from faculty and students, some sections within the book have been rewritten. Also, a number of corrections have been made, further improving the accuracy of this outstanding textbook.

This classic, time-honored introduction to the theory and practice of statistics modeling and inference reflects the changing focus of contemporary Statistics. Coverage begins with the more general nonparametric point of view and then looks at parametric models as submodels of the nonparametric ones which can be described smoothly by Euclidean parameters. Although some computational issues are discussed, this is very much a book on theory. It relates theory to conceptual and technical issues encountered in practice, viewing theory as suggestive for practice, not prescriptive. It shows readers how assumptions which lead to neat theory may be unrealistic in practice. Statistical Models, Goals, and Performance Criteria. Methods of Estimation. Measures of Performance, Notions of Optimality, and Construction of Optimal Procedures in Simple Situations. Testing Statistical Hypotheses: Basic Theory. Asymptotic Approximations. Multiparameter Estimation, Testing and Confidence Regions. A Review of Basic Probability Theory. More Advanced Topics in Analysis and Probability. Matrix Algebra. For anyone interested in mathematical statistics working in statistics, bio-statistics, economics, computer science, and mathematics.

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