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Mathematical statistics with resampling and R

Author: Laura Chihara; Tim Hesterberg
Publisher: Hoboken, NJ : John Wiley & Sons, Inc., 2019. ©2019
Edition/Format:   eBook : Document : English : Second editionView all editions and formats
Summary:
"Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. The second edition of Mathematical Statistics with Resampling and R combines modern resampling techniques and mathematical statistics. This book has been classroom-tested to ensure an accessible presentation, uses the powerful and flexible computer language R for  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Chihara, Laura, 1957-
Mathematical statistics with resampling and R.
Hoboken, NJ : Wiley, 2019
(DLC) 2018008774
(OCoLC)1029072291
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Laura Chihara; Tim Hesterberg
ISBN: 9781119416524 1119416523 9781119505969 1119505968 9781119416531 1119416531
OCLC Number: 1029061150
Description: 1 online resource (xv, 537 pages) : illustrations
Contents: Data and case studies --
Exploratory data analysis --
Introduction to hypothesis testing: permutation tests --
Sampling distributions --
Introduction to confidence intervals: the bootstrap --
Estimation --
More confidence intervals --
More hypothesis testing --
Regression --
Categorical data --
Bayesian methods --
One-way ANOVA --
Additional topics --
Appendices. Review of probability --
Probability distributions --
Distributions quick reference --
Solutions to selected exercises.
Responsibility: Laura M. Chihara, Carleton College, Tim C. Hesterberg, Google.

Abstract:

"Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. The second edition of Mathematical Statistics with Resampling and R combines modern resampling techniques and mathematical statistics. This book has been classroom-tested to ensure an accessible presentation, uses the powerful and flexible computer language R for data analysis and explores the benefits of modern resampling techniques. This book offers an introduction to permutation tests and bootstrap methods that can serve to motivate classical inference methods. The book strikes a balance between theory, computing, and applications, and the new edition explores additional topics including consulting, paired t test, ANOVA and Google Interview Questions. Throughout the book, new and updated case studies are included representing a diverse range of subjects such as flight delays, birth weights of babies, and telephone company repair times. These illustrate the relevance of the real-world applications of the material"--Publisher's description.

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