Purchase Introduction to Probability – 2nd Edition. Probability Theory and Stochastic Processes; Introduction to Probability Authors: George Roussas. Purchase An Introduction to Probability and Statistical Inference – 2nd Edition. Roussas, this book introduces readers with no prior knowledge in probability or. 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.
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Introduction to Probability
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Description Introduction to Probability, Second Edition, discusses probability theory in a mathematically rigorous, yet accessible way. This one-semester basic probability textbook explains important concepts of probability while providing useful exercises and examples of real world applications for students to consider. This edition demonstrates the applicability of probability to many human activities with examples and illustrations.
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After introducing fundamental probability concepts, the book proceeds to topics including conditional probability and independence; numerical characteristics of a random variable; special distributions; joint probability density function of two random variables and related quantities; joint moment generating function, covariance and correlation coefficient of two random variables; transformation of random variables; the Weak Law of Large Numbers; the Central Limit Theorem; and statistical inference.
Each section provides relevant proofs, followed by exercises and useful hints.
Answers to even-numbered exercises are given and detailed answers to all exercises are available to instructors on the book companion site. This book will be of interest to upper level undergraduate students and graduate level students in statistics, mathematics, engineering, computer science, operations research, actuarial science, biological sciences, economics, physics, and some of the social sciences.
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Table of contents Preface 1.
Some Motivating Examples 2. Some Fundamental Concepts 3. The Concept of Probability and Basic Results 4. Conditional Prbability and Independence 5. Numerical Characteristics of a Random Variable 6.
Some Special Distributions 7. Independence of Random Variables and Some Applications Transformation of Random Variables Readers should be comfortable with multiple integrals and, in spots, a little linear algebra.
The writing is clear and concise.
Introduction to Probability : George G. Roussas :
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 market I would be happy to adopt this book. 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.
Roussas earned a B. 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: 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.