MARC Record from marc_columbia

LEADER: 05411pam a2200325 a 4500
001 5404023
005 20221110031657.0
008 050415t20062006njua 001 0 eng
010 $a 2005047691
020 $a0131856626
035 $a(OCoLC)ocm59401216
035 $a(NNC)5404023
035 $a5404023
040 $aDLC$cDLC$dBAKER$dOrLoB-B
050 00 $aQA273$b.R83 2006
082 00 $a519.2$222
100 1 $aRoss, Sheldon M.$0http://id.loc.gov/authorities/names/n80131522
245 12 $aA first course in probability /$cSheldon Ross.
250 $a7th ed.
260 $aUpper Saddle River, N.J. :$bPearson Prentice Hall,$c[2006], ©2006.
300 $ax, 565 pages :$billustrations ;$c25 cm
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
500 $aIncludes index.
505 00 $g1.$tCombinatorial Analysis -- $g1.1.$tIntroduction -- $g1.2.$tThe Basic Principle of Counting -- $g1.3.$tPermutations -- $g1.4.$tCombinations -- $g1.5.$tMultinomial Coefficients -- $g1.6.$tThe Number of Integer Solutions of Equations* -- $g2.$tAxioms of Probability -- $g2.1.$tIntroduction -- $g2.2.$tSample Space and Events -- $g2.3.$tAxioms of Probability -- $g2.4.$tSome Simple Propositions -- $g2.5.$tSample Spaces Having Equally Likely Outcomes -- $g2.6.$tProbability as a Continuous Set Function* -- $g2.7.$tProbability as a Measure of Belief -- $g3.$tConditional Probability and Independence -- $g3.1.$tIntroduction -- $g3.2.$tConditional Probabilities -- $g3.3.$tBayes' Formula -- $g3.4.$tIndependent Events -- $g3.5.$tP(.[vertical bar]F) Is a Probability -- $g4.$tRandom Variables -- $g4.1.$tRandom Variables -- $g4.2.$tDiscrete Random Variables -- $g4.3.$tExpected Value -- $g4.4.$tExpectation of a Function of a Random Variable -- $g4.5.$tVariance -- $g4.6.$tThe Bernoulli and Binomial Random Variables -- $g4.6.1.$tProperties of Binomial Random Variables -- $g4.6.2.$tComputing the Binomial Distribution Function -- $g4.7.$tThe Poisson Random Variable -- $g4.7.1.$tComputing the Poisson Distribution Function -- $g4.8.$tOther Discrete Probability Distributions -- $g4.8.1.$tThe Geometric Random Variable -- $g4.8.2.$tThe Negative Binomial Random Variable -- $g4.8.3.$tThe Hypergeometric Random Variable -- $g4.8.4.$tThe Zeta (or Zipf) Distribution -- $g4.9.$tProperties of the Cumulative Distribution Function -- $g5.$tContinuous Random Variables -- $g5.1.$tIntroduction -- $g5.2.$tExpectation and Variance of Continuous Random Variables -- $g5.3.$tThe Uniform Random Variable -- $g5.4.$tNormal Random Variables -- $g5.4.1.$tThe Normal Approximation to the Binomial Distribution -- $g5.5.$tExponential Random Variables -- $g5.5.1.$tHazard Rate Functions -- $g5.6.$tOther Continuous Distributions -- $g5.6.1.$tThe Gamma Distribution -- $g5.6.2.$tThe Weibull Distribution -- $g5.6.3.$tThe Cauchy Distribution -- $g5.6.4.$tThe Beta Distribution -- $g5.7.$tThe Distribution of a Function of a Random Variable -- $g6.$tJointly Distributed Random Variables -- $g6.1.$tJoint Distribution Functions -- $g6.2.$tIndependent Random Variables -- $g6.3.$tSums of Independent Random Variables -- $g6.4.$tConditional Distributions: Discrete Case -- $g6.5.$tConditional Distributions: Continuous Case -- $g6.6.$tOrder Statistics -- $g6.7.$tJoint Probability Distribution of Functions of Random Variables -- $g6.8.$tExchangeable Random Variables -- $g7.$tProperties of Expectation -- $g7.1.$tIntroduction -- $g7.2.$tExpectation of Sums of Random Variables -- $g7.2.1.$tObtaining Bounds from Expectations via the Probabilistic Method -- $g7.2.2.$tThe Maximum-Minimums Identity -- $g7.3.$tMoments of the Number of Events that Occur -- $g7.4.$tCovariance, Variance of Sums, and Correlations -- $g7.5.$tConditional Expectation -- $g7.5.1.$tDefinitions -- $g7.5.2.$tComputing Expectations by Conditioning -- $g7.5.3.$tComputing Probabilities by Conditioning -- $g7.5.4.$tConditional Variance -- $g7.6.$tConditional Expectation and Prediction -- $g7.7.$tMoment Generating Functions -- $g7.7.1.$tJoint Moment Generating Functions -- $g7.8.$tAdditional Properties of Normal Random Variables -- $g7.8.1.$tThe Multivariate Normal Distribution -- $g7.8.2.$tThe Joint Distribution of the Sample Mean and Sample Variance -- $g7.9.$tGeneral Definition of Expectation -- $g8.$tLimit Theorems -- $g8.1.$tIntroduction -- $g8.2.$tChebyshev's Inequality and the Weak Law of Large Numbers -- $g8.3.$tThe Central Limit Theorem -- $g8.4.$tThe Strong Law of Large Numbers -- $g8.5.$tOther Inequalities -- $g8.6.$tBounding The Error Probability -- $g9.$tAdditional Topics in Probability -- $g9.1.$tThe Poisson Process -- $g9.2.$tMarkov Chains -- $g9.3.$tSurprise, Uncertainty, and Entropy -- $g9.4.$tCoding Theory and Entropy -- $g10.$tSimulation -- $g10.1.$tIntroduction -- $g10.2.$tGeneral Techniques for Simulating Continuous Random Variables -- $g10.2.1.$tThe Inverse Transformation Method -- $g10.2.2.$tThe Rejection Method -- $g10.3.$tSimulating from Discrete Distributions -- $g10.4.$tVariance Reduction Techniques -- $g10.4.1.$tUse of Antithetic Variables -- $g10.4.2.$tVariance Reduction by Conditioning -- $g10.4.3.$tControl Variates -- $gA.$tAnswers to Selected Problems -- $gB.$tSolutions to Self-Test Problems and Exercises.
650 0 $aProbabilities$vTextbooks.
852 00 $boff,eng$hQA273$i.R83 2006
852 00 $bmat$hQA273$i.R83 2006
852 00 $bmat$hQA273$i.R83 2006
852 00 $bmat$hQA273$i.R83 2006