Fundamentals of Probability: A First Course

  • Anirban┬áDasGupta

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

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Anirban DasGupta
    Pages 1-21
  3. Anirban DasGupta
    Pages 23-28
  4. Anirban DasGupta
    Pages 29-43
  5. Anirban DasGupta
    Pages 45-80
  6. Anirban DasGupta
    Pages 81-90
  7. Anirban DasGupta
    Pages 91-125
  8. Anirban DasGupta
    Pages 127-169
  9. Anirban DasGupta
    Pages 171-194
  10. Anirban DasGupta
    Pages 195-212
  11. Anirban DasGupta
    Pages 243-273
  12. Anirban DasGupta
    Pages 275-319
  13. Anirban DasGupta
    Pages 321-341
  14. Anirban DasGupta
    Pages 343-378
  15. Anirban DasGupta
    Pages 379-407
  16. Back Matter
    Pages 409-450

About this book

Introduction

This is a text encompassing all of the standard topics in introductory probability theory, together with a significant amount of optional material of emerging importance. The emphasis is on a lucid and accessible writing style, mixed with a large number of interesting examples of a diverse nature. The text will prepare students extremely well for courses in more advanced probability and in statistical theory and for the actuary exam.

The book covers combinatorial probability, all the standard univariate discrete and continuous distributions, joint and conditional distributions in the bivariate and the multivariate case, the bivariate normal distribution, moment generating functions, various probability inequalities, the central limit theorem and the laws of large numbers, and the distribution theory of order statistics. In addition, the book gives a complete and accessible treatment of finite Markov chains, and a treatment of modern urn models and statistical genetics. It includes 303 worked out examples and 810 exercises, including a large compendium of supplementary exercises for exam preparation and additional homework. Each chapter has a detailed chapter summary. The appendix includes the important formulas for the distributions in common use and important formulas from calculus, algebra, trigonometry, and geometry.

Anirban DasGupta is Professor of Statistics at Purdue University, USA. He has been the main editor of the Lecture Notes and Monographs series, as well as the Collections series of the Institute of Mathematical Statistics, and is currently the Co-editor of the Selected Works in Statistics and Probability series, published by Springer. He has been an associate editor of the Annals of Statistics, Journal of the American Statistical Association, Journal of Statistical Planning and Inference, International Statistical Review, Sankhya, and Metrika. He is the author of Asymptotic Theory of Statistics and Probability, 2008, and of 70 refereed articles on probability and statistics. He is a Fellow of the Institute of Mathematical Statistics.

Keywords

Conditional probability Markov chain Normal distribution Probability theory Random variable statistics

Authors and affiliations

  • Anirban┬áDasGupta
    • 1
  1. 1.Dept. Statistics & MathematicsPurdue UniversityWest LafayetteU.S.A.

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4419-5780-1
  • Copyright Information Springer-Verlag New York 2010
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4419-5779-5
  • Online ISBN 978-1-4419-5780-1
  • Series Print ISSN 1431-875X
  • About this book