Mathematical statistics with resampling and R / Laura M. Chihara (Carleton College), Tim C. Hesterberg (Google).
By: Chihara, Laura [author.]
Contributor(s): Hesterberg, Tim [author.]
Language: English Publisher: Hoboken, NJ : John Wiley & Sons, Inc., ©2022Edition: Second editionDescription: xvi, 559 pages : illustrations ; 23 cmContent type: text Media type: unmediated Carrier type: volumeISBN: 9781119874034Subject(s): Resampling (Statistics) | Statistics | Statistics -- Data processing | Mathematical statistics -- Data processing | R (Computer program language)Genre/Form: Electronic books. DDC classification: 519.54 LOC classification: QA278.8Online resources: Full text is available at Wiley Online Library Click here to view Summary: This thoroughly updated second edition combines the latest software applications with the benefits of modern resampling techniques 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. This new edition: • Puts the focus on statistical consulting that emphasizes giving a client an understanding of data and goes beyond typical expectations • Presents new material on topics such as the paired t test, Fisher's Exact Test and the EM algorithm • Offers a new section on "Google Interview Questions" that illustrates statistical thinking • Provides a new chapter on ANOVA • Contains more exercises and updated case studies, data sets, and R code Written for undergraduate students in a mathematical statistics course as well as practitioners and researchers, the second edition of Mathematical Statistics with Resampling and R presents a revised and updated guide for applying the most current resampling techniques to mathematical statistics.| Item type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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HIGH SCHOOL LIBRARY - SHS | HIGH SCHOOL LIBRARY - SHS SUBJECT REFERENCE | 519.54 C4356 2022 (Browse shelf) | Available |
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| 516 R37 2018 Schaum's outline of theory and problems of geometry : includes plane, analytic, transformational, and solid geometries / | 516.24 M874 2018 Schaum's outline of theory and problems of trigonometry : with calculator-based solutions / | 519.5 Sp43 2018 Schaum's outlines statistics / | 519.54 C4356 2022 Mathematical statistics with resampling and R / | 519.54 D3952 2023 M-statistics : optimal statistical inference for a small sample / | 530 C979 2015 Introduction to physics and WileyPLUS set / | 530 Se699 2018 General physics / |
ABOUT THE AUTHORS
LAURA M. CHIHARA, PHD, is Professor of Mathematics and Statistics at Carleton College. She has extensive experience teaching mathematics and statistics and has worked as Educational Services Supervisor at Insightful Corporation.
TIM C. HESTERBERG, PHD, is Senior Data Scientist at Google. He was a senior research scientist for Insightful Corporation and led the development of S+Resample and other S+ and R software.
Includes bibliographical references and index.
This thoroughly updated second edition combines the latest software applications with the benefits of modern resampling techniques
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. This new edition:
• Puts the focus on statistical consulting that emphasizes giving a client an understanding of data and goes beyond typical expectations
• Presents new material on topics such as the paired t test, Fisher's Exact Test and the EM algorithm
• Offers a new section on "Google Interview Questions" that illustrates statistical thinking
• Provides a new chapter on ANOVA
• Contains more exercises and updated case studies, data sets, and R code
Written for undergraduate students in a mathematical statistics course as well as practitioners and researchers, the second edition of Mathematical Statistics with Resampling and R presents a revised and updated guide for applying the most current resampling techniques to mathematical statistics.
Description based on print version record and CIP data provided by publisher.
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