
Introduction to Probability
George G. Roussas(Author)
Academic Press
Published on 19. October 2006
Book
Hardback
400 pages
978-0-12-088595-4 (ISBN)
Article exhausted; check for reprint
Description
Roussas's Introduction to Probability features exceptionally clear explanations of the mathematics of probability theory and explores its diverse applications through numerous interesting and motivational examples. It provides a thorough introduction to the subject for professionals and advanced students taking their first course in probability. The content is based on the introductory chapters of Roussas's book, An Intoduction to Probability and Statistical Inference, with additional chapters and revisions.
Reviews / Votes
the first seven chapters can be used as one term undergraduate course in probability. I am satisfied with the topics covered in each chapter and the order in which they are presented. Numerous solved examples and exercises are provided in each chapter. They support concepts well, and they are of high quality. The examples and exercises are carefully selected and are even better than many texts currently available in the marketI would be happy to adopt this book. -Subash Bagui Univ of West Florida "I feel this book covers the topics better and in a more easy to understand way with the conversational tone. There are a lot more examples and I like that the exercises are not too technologically dependent. I would definitely adopt this for my Intro Probability course. The first eight chapters are a perfect fit. -Pat Goeters Auburn UniversityMore details
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
College/higher education
Advanced undergraduate and graduate students in mathematics, physics, engineering, statistics, actuarial science, operations research, and computer science.
Illustrations
Illustrated
Dimensions
Height: 235 mm
Width: 191 mm
Weight
980 gr
ISBN-13
978-0-12-088595-4 (9780120885954)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
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George G. Roussas
Introduction to Probability
Book
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George Roussas
Introduction to Probability
Book
09/2006
Academic Press
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Introduction to Probability
E-Book
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Person
George G. Roussas earned a B.S. in Mathematics with honors from the University of Athens, Greece, and a Ph.D. in Statistics from the University of California, Berkeley. As of July 2014, he is a Distinguished Professor Emeritus of Statistics at the University of California, Davis. Roussas is the author of five books, the author or co-author of five special volumes, and the author or co-author of dozens of research articles published in leading journals and special volumes. He is a Fellow of the following professional societies: The American Statistical Association (ASA), the Institute of Mathematical Statistics (IMS), The Royal Statistical Society (RSS), the American Association for the Advancement of Science (AAAS), and an Elected Member of the International Statistical Institute (ISI); also, he is a Corresponding Member of the Academy of Athens. Roussas was an associate editor of four journals since their inception, and is now a member of the Editorial Board of the journal Statistical Inference for Stochastic Processes. Throughout his career, Roussas served as Dean, Vice President for Academic Affairs, and Chancellor at two universities; also, he served as an Associate Dean at UC-Davis, helping to transform that institution's statistical unit into one of national and international renown. Roussas has been honored with a Festschrift, and he has given featured interviews for the Statistical Science and the Statistical Periscope. He has contributed an obituary to the IMS Bulletin for Professor-Academician David Blackwell of UC-Berkeley, and has been the coordinating editor of an extensive article of contributions for Professor Blackwell, which was published in the Notices of the American Mathematical Society and the Celebratio Mathematica.
Content
1. Some Motivating Examples
2. Some Fundamental Concepts
3. The Concept of Probability and Basic Results
4. Conditional Probability and Independence
5. Numerical Characteristics of a Random Variable
6. Some Special Distributions
7. Joint Probability Density Function of Two Random Variables and Related Quantities
8. Joint Moment Generating Function, Covariance and Correlation Coefficient of Two Random Variables
9. Some Generalizations to k Random Variables, and Three Multivariate Distributions
10. Independence of Random Variables and Some Applications
11. Transformation of Random Variables
12. Two Modes of Convergence, the Weak Law of Large Numbers, the Central Limit Theorem, and Further Results
13. An Overview of Statistical Inference
Appendix
Tables
Some Notation and Abbreviations
Answers to the Even-numbered Exercises
2. Some Fundamental Concepts
3. The Concept of Probability and Basic Results
4. Conditional Probability and Independence
5. Numerical Characteristics of a Random Variable
6. Some Special Distributions
7. Joint Probability Density Function of Two Random Variables and Related Quantities
8. Joint Moment Generating Function, Covariance and Correlation Coefficient of Two Random Variables
9. Some Generalizations to k Random Variables, and Three Multivariate Distributions
10. Independence of Random Variables and Some Applications
11. Transformation of Random Variables
12. Two Modes of Convergence, the Weak Law of Large Numbers, the Central Limit Theorem, and Further Results
13. An Overview of Statistical Inference
Appendix
Tables
Some Notation and Abbreviations
Answers to the Even-numbered Exercises