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Modern Mathematical Statistics with Applications

  • Jay L. Devore
  • Kenneth N. Berk

Part of the Springer Texts in Statistics book series (STS)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Jay L. Devore, Kenneth N. Berk
    Pages 1-49
  3. Jay L. Devore, Kenneth N. Berk
    Pages 50-95
  4. Jay L. Devore, Kenneth N. Berk
    Pages 96-157
  5. Jay L. Devore, Kenneth N. Berk
    Pages 158-231
  6. Jay L. Devore, Kenneth N. Berk
    Pages 232-283
  7. Jay L. Devore, Kenneth N. Berk
    Pages 284-330
  8. Jay L. Devore, Kenneth N. Berk
    Pages 331-381
  9. Jay L. Devore, Kenneth N. Berk
    Pages 382-424
  10. Jay L. Devore, Kenneth N. Berk
    Pages 425-483
  11. Jay L. Devore, Kenneth N. Berk
    Pages 484-551
  12. Jay L. Devore, Kenneth N. Berk
    Pages 552-612
  13. Jay L. Devore, Kenneth N. Berk
    Pages 613-722
  14. Jay L. Devore, Kenneth N. Berk
    Pages 723-757
  15. Jay L. Devore, Kenneth N. Berk
    Pages 758-786
  16. J. L. Devore, K. N. Berk
    Pages E1-E1
  17. Back Matter
    Pages 787-845

About this book

Introduction

Many mathematical statistics texts are heavily oriented toward a rigorous mathematical development of probability and statistics, without much attention paid to how statistics is actually used.. In contrast, Modern Mathematical Statistics with Applications, Second Edition strikes a balance between mathematical foundations and statistical practice. In keeping with the recommendation that every math student should study statistics and probability with an emphasis on data analysis, accomplished authors Jay Devore and Kenneth Berk make statistical concepts and methods clear and relevant through careful explanations and a broad range of applications involving real data.

 

The main focus of the book is on presenting and illustrating methods of inferential statistics that are useful in research.  It begins with a chapter on descriptive statistics that immediately exposes the reader to real data.  The next six chapters develop the probability material that bridges the gap between descriptive and inferential statistics.  Point estimation, inferences based on statistical intervals, and hypothesis testing are then introduced in the next three chapters.  The remainder of the book explores the use of this methodology in a variety of more complex settings.

 

This edition includes a plethora of new exercises, a number of which are similar to what would be encountered on the actuarial exams that cover probability and statistics. Representative applications include investigating whether the average tip percentage in a particular restaurant exceeds the standard 15%, considering whether the flavor and aroma of Champagne are affected by bottle temperature or type of pour, modeling the relationship between college graduation rate and average SAT score, and assessing the likelihood of O-ring failure in space shuttle launches as related to launch temperature.

 

Other features include:

- An extensive range of applications that will appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and business, economics, and quantitative social science students.

- Nearly 1,500 exercises to help students master the material and better understand sophisticated concepts and arguments.

- An emphasis on the importance of statistical software, including output from the statistical software packages Minitab, R, and SAS.

Keywords

Descriptive statistics Inference Point estimation Probability Regression and correlation

Authors and affiliations

  • Jay L. Devore
    • 1
  • Kenneth N. Berk
    • 2
  1. 1.Statistics DepartmentCalifornia Polytechnic State UniversitySan Luis ObispoUSA
  2. 2.Department of MathematicsIllinois State UniversityNormalUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-0391-3
  • Copyright Information Springer Science+Business Media, LLC 2012
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4614-0390-6
  • Online ISBN 978-1-4614-0391-3
  • Series Print ISSN 1431-875X
  • Series Online ISSN 2197-4136
  • Buy this book on publisher's site