Mathematical Statistics with Resampling and R (eBook)

Laura M. Chihara, Tim C. Hesterberg (Autoren)

eBook Download: PDF

2018 | 2. Auflage
Wiley (Verlag)
978-1-119-41652-4 (ISBN)

Infos

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 "e;Google Interview Questions"e; 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.

Autor

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.

Produkt-Details

• Erscheint lt. Verlag: 17.9.2018
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• Schlagworte: accuracy of the central limit theorem</p> • Assumptions • box plots • calculating sampling distributions • case studies on Mathematical statistics with resampling and R • continuity correction for discrete random variables • empirical cumulative distribution functions • Exploratory data analysis • General Social Survey • guide to Mathematical statistics with resampling and R • hypothesis testing • Implementation issues • introduction to hypothesis testing • <p>Text on Mathematical statistics with resampling and R • matched pairs • Mathematische Statistik • mobile ads optimization • numeric summaries • parameters and statistics • Permutation Tests • Probability & Mathematical Statistics • quantiles and normal quantile plots • Resource to Mathematical statistics with resampling and R • R (Programm) • Sampling distributions • scatter plots • skewness and kurtosis • Statistical Software / R • Statistics • Statistics - Text & Reference • Statistik • Statistik / Lehr- u. Nachschlagewerke • Statistiksoftware / R • the central limit theorem • understanding Mathematical statistics with resampling and R • Wahrscheinlichkeitsrechnung • Wahrscheinlichkeitsrechnung u. mathematische Statistik
• ISBN-10: 1-119-41652-3 / 1119416523
• ISBN-13: 978-1-119-41652-4 / 9781119416524