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(Ebook) Modern Mathematical Statistics with Applications by Jay L. Devore, Kenneth N. Berk, Matthew A. Carlton ISBN 9783030551551, 3030551555

  • SKU: EBN-36497088
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Authors:Jay L. Devore, Kenneth N. Berk, Matthew A. Carlton
Pages:1029 pages.
Year:2021
Editon:3rd ed. 2021
Publisher:Springer
Language:english
File Size:53.4 MB
Format:epub
ISBNS:9783030551551, 3030551555
Categories: Ebooks

Product desciption

(Ebook) Modern Mathematical Statistics with Applications by Jay L. Devore, Kenneth N. Berk, Matthew A. Carlton ISBN 9783030551551, 3030551555

This 3rd edition of Modern Mathematical Statistics with Applications tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear and current exposition of statistical concepts and methodology, including many examples and exercises based on real data gleaned from publicly available sources. The selection of scenarios for our examples and exercises are based on information in recent articles: Use of the “Big Mac index” by the publication The Economist as a humorous way to compare product costs across nations Visualizing how the concentration of lead levels in cartridges varies for each of five brands of e-cigarettes Describing the distribution of grip size among surgeons and how it impacts their ability to use a particular brand of surgical stapler Estimating the true average odometer reading of used Porsche Boxsters listed for sale on www.cars.com Comparing head acceleration after impact when wearing a football helmet with acceleration without a helmet Investigating the relationship between body mass index and foot load while running The main focus of the book is on presenting and illustrating methods of inferential statistics used by investigators in a wide variety of disciplines, from actuarial science all the way to zoology. It begins with a chapter on descriptive statistics that immediately exposes the reader to the analysis of real data. The next six chapters develop the probability material that facilitates the transition from simply describing data to drawing formal conclusions based on inferential methodology. Point estimation, the use of statistical intervals, and hypothesis testing are the topics of the first three inferential chapters. The remainder of the book explores the use of these methods in a variety of more complex settings. This edition includes many new examples and exercises as well as an introduction to the simulation of events and probability distributions.
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