A first course in probability / (Record no. 756)

MARC details
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20210909134750.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 090607s1998 njua 001 0 eng
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 97017297
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780137463145
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0137463146
035 ## - SYSTEM CONTROL NUMBER
System control number (Sirsi) u1690
040 ## - CATALOGING SOURCE
Original cataloging agency EG-CaNU
Transcribing agency EG-CaNU
Modifying agency EG-CaNU
042 ## - AUTHENTICATION CODE
Authentication code ncode
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 510.2
Edition number 22
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Ross, Sheldon M.
9 (RLIN) 2348
245 12 - TITLE STATEMENT
Title A first course in probability /
Statement of responsibility, etc. Sheldon M Ross.
250 ## - EDITION STATEMENT
Edition statement 5th ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Upper Saddle River, N.J. :
Name of publisher, distributor, etc. Prentice Hall,
Date of publication, distribution, etc. c1998.
300 ## - PHYSICAL DESCRIPTION
Extent xiv, 514 p. :
Other physical details ill. ;
Dimensions 25 cm.
500 ## - GENERAL NOTE
General note Includes index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note combinatorial analysis -- 1.1 introduction -- 1.2 the basic principle of counting -- 1.3 permutations -- 1.4 combinations -- 1.5 multinomial coefficients -- 1.6 on the distribution of balls in urns* -- summary -- problems -- theoretical exercises -- self-test problems and exercises -- 2 axioms of probability -- 2.1 introduction -- 2.2 sample space and events -- 2.3 axioms of probability -- 2.4 some simple propositions -- 2.5 sample spaces having equally likely outcomes -- 2.6 probability as a continuous set function* -- 2.7 probability as a measure of belief -- summary -- problems -- theoretical exercises -- self-test problems and exercises -- 3 conditional probability and independence -- 3.1 introduction -- 3.2 conditional probabilities -- 3.3 bayes' formula -- 3.4 independent events -- 3.5 p(.\f) is a probability(*) -- summary -- problems -- theoretical exercises -- self-test problems and exercises -- 4 random variables -- 4.1 random variables -- 4.2 distribution functions -- 4.3 discrete random variables -- 4.4 expected value -- 4.5 expectation of a function of a random variable -- 4.6 variance -- 4.7 the bernoulli and binomial random variables -- 4.7.1 properties of binomial random variables -- 4.7.2 computing the binomial distribution function -- 4.8 the poisson random variable -- 4.8.1 computing the poisson distribution function -- 4.9 other discrete probability distribution -- 4.9.1 the geometric random variable -- 4.9.2 the negative binomial random variable -- 4.9.3 the hypergeometric random variable -- 4.9.4 the zeta (or zipf) distribution -- summary -- problems -- theoretical exercises -- self-test problems and exercises -- 5 continuous random variables -- 5.1 introduction -- 5.2 expectation and variance of continuous random variables -- 5.3 the uniform random variable -- 5.4 normal random variables -- 5.4.1 the normal approximation to the binomial distribution -- 5.5 exponential random variables -- 5.5.1 hazard rate functions -- 5.6 other continuous distributions -- 5.6.1 the gamma distribution -- 5.6.2 the weibull distribution -- 5.6.3 the cauchy distribution -- 5.6.4 the beta distribution -- 5.7 the distribution of a function of a random variable -- summary -- problems -- theoretical exercises -- self-test problems and exercises -- 6 jointly distributed random variables -- 6.1 joint distribution functions -- 6.2 independent random variables -- 6.3 sums of independent random variables -- 6.4 conditional distributions: discrete case -- 6.5 conditional distributions: continuous case -- 6.6 order statistics* -- 6.7 joint probability distribution of functions of random variables -- 6.8 exchangeable random variables* -- summary -- problems -- theoretical exercises -- self-test problem and exercises -- 7 properties of expectation -- 7.1 introduction -- 7.2 expectation of sums of random variables -- 7.3 covariance, variance of sums, and correlations -- 7.4 conditional expectation -- 7.4.1 definitions -- 7.4.2 computing expectations by conditioning -- 7.4.3 computing probabilities by conditioning -- 7.4.4 conditional variance -- 7.5 conditional expectation and prediction -- 7.6 moment generating functions -- 7.6.1 joint moment generating functions -- 7.7 additional properties of normal random variables -- 7.7.1 the multivariate normal distribution -- 7.7.2 the joint distribution of the sample mean and sample variance -- 7.8 general definition of expectation(*) -- summary -- problems -- theoretical exercises -- self-test problems and exercises -- 8 limit theorems -- 8.1 introduction -- 8.2 chebyshev's inequality and the weak law of large numbers -- 8.3 the central limit theorem -- 8.4 the strong law of large numbers -- 8.5 other inequalities -- 8.6 bounding the error probability when approximating a sum of independent bernoulli random variables by a poisson -- summary -- problems -- theoretical exercises -- self-test problems and exercises -- 9 additional topics in probability -- 9.1 the poisson process -- 9.2 markov chains -- 9.3 surprise, uncertainty, and entropy -- 9.4 coding theory and entropy -- summary -- theoretical exercises and problems -- self-test problems and exercises -- references -- 10 simulation -- 10.1 introduction -- 10.2 general techniques for simulating continuous random variables -- 10.2.1 the inverse transformation method -- 10.2.2 the rejection method -- 10.3 simulating from discrete distributions -- 10.4 variance reduction techniques -- 10.4.1 use of antithetic variables -- 10.4.2 variance reduction by conditioning -- 10.4.3 control variates -- summary -- problems -- self-test problems and exercises -- references -- appendix a answers to selected problems -- appendix b solutions to self-test problems and exercise -- index.
520 ## - SUMMARY, ETC.
Summary, etc. This market leader is written as an elementary introduction to the mathematical theory of probability for students in mathematics, engineering, and the sciences who possess the prerequisite knowledge of elementary calculus. A major thrust of the Fifth Edition has been to make the book more accessible to today's students. The exercise sets have been revised to include more simple, mechanical problems and a new section of Self-Test Problems with fully worked out solutions conclude each chapter. In addition, many new applications have been added to demonstrate the importance of probability in real situations. A software diskette, referenced in text and packaged with each copy of the book, provides an easy to use tool for students to derive probabilities for binomial, Poisson, and normal random variables, illustrate and explore the central limit theorem, work with the strong law of large numbers, and more.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Probabilities.
9 (RLIN) 2349
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Dewey Decimal Classification     Main library Main library General Stacks 01/26/2020 GIFT 510.2 / RO.F 1998 004221 11/24/2019 1 11/24/2019 Books