An Introduction to Probability and Statistical Inference - 1st Edition

An Introduction to Probability and Statistical Inference

1st Edition

Authors: George Roussas George Roussas
Imprint: Academic Press
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Description

Roussas introduces readers with no prior knowledge in probability or statistics, to a thinking process to guide them toward the best solution to a posed question or situation. An Introduction to Probability and Statistical Inference provides a plethora of examples for each topic discussed, giving the reader more experience in applying statistical methods to different situations.

"The text is wonderfully written and has the most comprehensive range of exercise problems that I have ever seen." — Tapas K. Das, University of South Florida

"The exposition is great; a mixture between conversational tones and formal mathematics; the appropriate combination for a math text at [this] level. In my examination I could find no instance where I could improve the book." — H. Pat Goeters, Auburn, University, Alabama

Key Features

  • Contains more than 200 illustrative examples discussed in detail, plus scores of numerical examples and applications
  • Chapters 1-8 can be used independently for an introductory course in probability
  • Provides a substantial number of proofs

Readership

Researchers and practitioners in engineering, business, social sciences or agriculture.

Table of Contents

Some Motivating Examples and Some Fundamental Concepts; The Concept of Probability and Some Basic Results; Numerical Characteristics of a Random Variable, Some Special Random Variables; Joint and Conditionalp.d.f:s, Conditional Expectation and Variance, Moment Generating Function, Covariance and Correlation Coefficient; Independence of Random Variables and Some Applications; Transformation of Random Variables; Modes of Convergence of Random Variables, Applications; An Overview of Statistical Inference; Point Estimation; Confidence Intervals and Confidence Regions; Testing Hypotheses; More About Testing Hypotheses; A Simple Linear Regression Model; Two Analysis of Variance Models; Some Topics in Nonparametric Inference

Details

Language:
English
Imprint:
Academic Press
eBook ISBN:
9780080495750

About the Author

George Roussas

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.

Affiliations and Expertise

University of California, Davis, USA

George Roussas

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.

Affiliations and Expertise

University of California, Davis, USA

Reviews

Roussas introduces readers with no prior knowledge in probability or statistics, to a thinking process to guide them toward the best solution to a posed question or situation. An Introduction to Probability and Statistical Inference provides a plethora of examples for each topic discussed, giving the reader more experience in applying statistical methods to different situations. "The text is wonderfully written and has the most comprehensive range of exercise problems that I have ever seen." — Tapas K. Das, University of South Florida "The exposition is great; a mixture between conversational tones and formal mathematics; the appropriate combination for a math text at [this] level. In my examination I could find no instance where I could improve the book." — H. Pat Goeters, Auburn, University, Alabama