A First Course in Probability

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Prentice Hall, 2002 - Mathematics - 520 pages
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This market-leading introduction to probability features exceptionally clear explanations of the mathematics of probability theory and explores its many diverse applications through numerous interesting and motivational examples. The outstanding problem sets are a hallmark feature of this book. Provides clear, complete explanations to fully explain mathematical concepts. Features subsections on the probabilistic method and the maximum-minimums identity. Includes many new examples relating to DNA matching, utility, finance, and applications of the probabilistic method. Features an intuitive treatment of probability—intuitive explanations follow many examples. The Probability Models Disk included with each copy of the book, contains six probability models that are referenced in the book and allow readers to quickly and easily perform calculations and simulations.

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Contents

AXIOMS OF PROBABILITY
24
CONDITIONAL PROBABILITY AND INDEPENDENCE
64
RANDOM VARIABLES
122
Copyright

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Sheldon M. Ross
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Sheldon M. Ross
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Common terms and phrases

approximately assume ball number binomial random variable black balls cards central limit theorem Chapter Chebyshev's inequality components compute conditional probability Consider contains continuous random variable defined denote the event denote the number desired probability dice discrete random variable distribution function distribution with parameters equal Equation Example expected number expected value exponential random variable Find the probability first flips follows function f given Hence HINT identically distributed independent trials inequality joint density function joint probability large numbers least Let X denote nonnegative normal random variable normally distributed number of successes obtain occur P(EF pair percent permutation player Poisson random variable preceding prob probability density function probability mass function Proposition random number random vari randomly chosen result sample space sequence Show simulate Solution Let Suppose tion uniformly distributed Var(X variable with mean variable with parameters variance white balls wins

About the author (2002)

Sheldon M. Ross is the Epstein Chair Professor at the Department of Industrial and Systems Engineering, University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968 and was formerly a Professor at the University of California, Berkeley, from 1976 until 2004. He has published more than 100 articles and a variety of textbooks in the areas of statistics and applied probability, including Topics in Finite and Discrete Mathematics (2000), Introduction to Probability and Statistics for Engineers and Scientists, Fourth Edition (2009), A First Course in Probability, Eighth Edition (2009), and Introduction to Probability Models, Tenth Edition (2009), among others. Dr Ross serves as the editor for Probability in the Engineering and Informational Sciences.

Bibliographic information

QR code for A First Course in Probability
TitleA First Course in Probability
AuthorSheldon M. Ross
Edition6, illustrated
PublisherPrentice Hall, 2002
Original fromthe University of Michigan
DigitizedAug 26, 2011
ISBN0130338516, 9780130338518
Length520 pages
Subjects ›  › 

Mathematics / Probability & Statistics / General
  
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