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Eugene Demidenko [Eugene Demidenko] - Advanced Statistics with Applications in R

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Eugene Demidenko [Eugene Demidenko] Advanced Statistics with Applications in R

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Advanced Statistics with Applications in R fills the gap between several excellent theoretical statistics textbooks and many applied statistics books where teaching reduces to using existing packages. This book looks at what is under the hood. Many statistics issues including the recent crisis with p-value are caused by misunderstanding of statistical concepts due to poor theoretical background of practitioners and applied statisticians. This book is the product of a forty-year experience in teaching of probability and statistics and their applications for solving real-life problems.

There are more than 442 examples in the book: basically every probability or statistics concept is illustrated with an example accompanied with an R code. Many examples, such as Who said ? What team is better? The fall of the Roman empire, James Bond chase problem, Black Friday shopping, Free fall equation: Aristotle or Galilei, and many others are intriguing. These examples cover biostatistics, finance, physics and engineering, text and image analysis, epidemiology, spatial statistics, sociology, etc.

Advanced Statistics with Applications in R teaches students to use theory for solving real-life problems through computations: there are about 500 R codes and 100 datasets. These data can be freely downloaded from the authors website dartmouth.edu/~eugened.

This book is suitable as a text for senior undergraduate students with major in statistics or data science or graduate students. Many researchers who apply statistics on the regular basis find explanation of many fundamental concepts from the theoretical perspective illustrated by concrete real-world applications.

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Table of Contents List of Tables Chapter 1 Chapter 2 Chapter 4 Chapter - photo 1
Table of Contents List of Tables Chapter 1 Chapter 2 Chapter 4 Chapter - photo 2
Table of Contents
List of Tables
  1. Chapter 1
  2. Chapter 2
  3. Chapter 4
  4. Chapter 6
  5. Chapter 7
  6. Chapter 8
List of Illustrations
  1. Chapter 1
  2. Chapter 2
  3. Chapter 3
  4. Chapter 4
  5. Chapter 5
  6. Chapter 6
  7. Chapter 7
  8. Chapter 8
  9. Chapter 9
  10. Chapter 10
Guide
Pages

WILEY SERIES IN PROBABILITY AND STATISTICS

Established by Walter A. Shewhart and Samuel S. Wilks

Editors: David J. Balding, Noel A. C. Cressie, Garrett M. Fitzmaurice, Geof H. Givens, Harvey Goldstein, Geert Molenberghs, David W. Scott, Adrian F. M. Smith, Ruey S. Tsay

Editors Emeriti: J. Stuart Hunter, Iain M. Johnstone, Joseph B. Kadane, Jozef L. Teugels

The Wiley Series in Probability and Statistics is well established and authoritative. It covers many topics of current research interest in both pure and applied statistics and probability theory. Written by leading statisticians and institutions, the titles span both stateoftheart developments in the field and classical methods.

Reflecting the wide range of current research in statistics, the series encompasses applied, methodological and theoretical statistics, ranging from applications and new techniques made possible by advances in computerized practice to rigorous treatment of theoretical approaches. This series provides essential and invaluable reading for all statisticians, whether in academia, industry, government, or research.

Advanced Statistics with Applications in R

Eugene Demidenko

Dartmouth College

Copyright This edition first published 2020 2020 John Wiley Sons Inc All - photo 3

Copyright

This edition first published 2020

2020 John Wiley & Sons Inc.

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.

The right of Eugene Demidenko to be identified as the author of this work has been asserted in accordance with law.

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John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA

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For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com.

Wiley also publishes its books in a variety of electronic formats and by printondemand. Some content that appears in standard print versions of this book may not be available in other formats.

Limit of Liability/Disclaimer of Warranty

While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.

Library of Congress CataloginginPublication Data

Names: Demidenko, Eugene, 1948 author.

Title: Advanced statistics with applications in R / Eugene Demidenko

(Dartmouth College).

Description: Hoboken, NJ : Wiley, 2020. | Series: Wiley series in probability

and statistics | Includes bibliographical references and index. |

Identifiers: LCCN 2019015124 (print) | LCCN 2019019543 (ebook) | ISBN

9781118594131 (Adobe PDF) | ISBN 9781118594612 (ePub) | ISBN 9781118387986

(hardback)

Subjects: LCSH: Mathematical statisticsData processingProblems,

exercises, etc. | StatisticsData processingProblems, exercises, etc. |

R (Computer program language)

Classification: LCC QA276.45.R3 (ebook) | LCC QA276.45.R3 D4575 2019 (print)

| DDC 519.5dc23

LC record available at https://lccn.loc.gov/2019015124

Cover design by Wiley

Cover image: Courtesy of Eugene Demidenko


Dedication

To my family


Why I Wrote This Book

My favorite part of the recent American Statistical Association (ASA) statement on the Picture 4value [] without single reallife data example. On the other hand, there are numerous recipestyle statistics textbooks where theoretical considerations, assumptions, and explanations are minimized. This book fills that gap.

Statistical software has become so convenient and versatile these days that many use it without understanding the underlying principles. Unfortunately, R packages do not explain the algorithms and mathematics behind computations, greatly contributing to a superficial understanding making statistics too easy. Many times, to my question How did you compute this, what is the algorithm, I hear the answer, I found a program on the Internet. Hopefully, this book will break the unwanted trend of such statistics consumption.

I have often been confronted with the question comparing statistics with driving a car: Why do we need to know how the car works? Well, because statistics is not a car: the chance of the car breaking is slim, but starting with the wrong statistical analysis is almost guaranteed without solid understanding of statistics background and implied limitations. In this book, we look at what is under the hood.

Each term I start my first class in statistics at Dartmouth with the following statement:

Mathematics is the queen and statistics is the king of all sciences

Indeed, mathematics is the idealistic model of the world: one line goes through a pair of points, the perimeter of a polygon converges to Advanced Statistics with Applications in R - image 5 when the number of edges goes to infinity, etc. Statistics fills mathematics with life. Due to an unavoidable measurement error, one point turns into a cloud of points. How does one draw a line through two clouds of points? How does one measure Picture 6

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