Introduction to Probability
Autor George G. Roussasen Limba Engleză Hardback – 20 ian 2014
This edition demonstrates the applicability of probability to many human activities with examples and illustrations. 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.
- Demonstrates the applicability of probability to many human activities with examples and illustrations
- Discusses probability theory in a mathematically rigorous, yet accessible way
- Each section provides relevant proofs, and is followed by exercises and useful hints
- Answers to even-numbered exercises are provided and detailed answers to all exercises are available to instructors on the book companion site
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Specificații
ISBN-13: 9780128000410
ISBN-10: 0128000414
Pagini: 546
Ilustrații: Illustrated
Dimensiuni: 191 x 235 x 28 mm
Greutate: 0.89 kg
Ediția:2. Auflage.
Editura: ELSEVIER SCIENCE
ISBN-10: 0128000414
Pagini: 546
Ilustrații: Illustrated
Dimensiuni: 191 x 235 x 28 mm
Greutate: 0.89 kg
Ediția:2. Auflage.
Editura: ELSEVIER SCIENCE
Public țintă
Advanced undergraduate and graduate students in mathematics, physics, engineering, statistics, actuarial science, operations research, and computer science.Cuprins
Preface1. Some Motivating Examples2. Some Fundamental Concepts 3. The Concept of Probability and Basic Results4. Conditional Probability and Independence5. Numerical Characteristics of a Random Variable 6. Some Special Distributions7. 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 AppendixSome Notation and Abbreviations Answers to the Even-Numbered ExercisesIndex
Recenzii
"...a very traditional mathematics text on the topic of probability. Readers should be comfortable with multiple integrals and, in spots, a little linear algebra. The writing is clear and concise." --MAA.org, August 18 2014