LEADER 04546nam 2200745Ia 450 001 9910877699503321 005 20200520144314.0 010 $a9786613274021 010 $a9781283274029 010 $a1283274027 010 $a9781118165966 010 $a1118165969 010 $a9781118165836 010 $a1118165837 035 $a(CKB)1000000000013752 035 $a(EBL)818937 035 $a(OCoLC)757394297 035 $a(SSID)ssj0000540383 035 $a(PQKBManifestationID)11314750 035 $a(PQKBTitleCode)TC0000540383 035 $a(PQKBWorkID)10581864 035 $a(PQKB)10850129 035 $a(SSID)ssj0000644272 035 $a(PQKBManifestationID)12264796 035 $a(PQKBTitleCode)TC0000644272 035 $a(PQKBWorkID)10675598 035 $a(PQKB)11308154 035 $a(MiAaPQ)EBC818937 035 $a(Perlego)2773354 035 $a(EXLCZ)991000000000013752 100 $a20110625d2008 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aProbability and statistics for computer science /$fJames L. Johnson 210 $aHoboken, NJ $cWiley Interscience$dc2008 215 $a1 online resource (764 p.) 300 $aDescription based upon print version of record. 311 08$a9780470383421 311 08$a0470383429 311 08$a9780471326724 311 08$a0471326720 320 $aIncludes bibliographical references (p. 733-738) and index. 327 $aProbability and Statistics for Computer Science; Contents; Preface; 1 Combinatorics and Probability; 1.1 Combinatorics; 1.1.1 Sampling without replacement; 1.1.2 Sampling with replacement; 1.2 Summations; 1.3 Probability spaces and random variables; 1.4 Conditional probability; 1.5 Joint distributions; 1.6 Summary; 2 Discrete Distributions; 2.1 The Bernoulli and binomial distributions; 2.2 Power series; 2.3 Geometric and negative binomial forms; 2.4 The Poisson distribution; 2.5 The hypergeometric distribution; 2.6 Summary; 3 Simulation; 3.1 Random number generation 327 $a3.2 Inverse transforms and rejection filters3.3 Client-server systems; 3.4 Markov chains; 3.4.1 Irreducible aperiodic Markov chains; 3.4.2 Convergence properties; 4 Discrete Decision Theory; 4.1 Decision methods without samples; 4.2 Statistics and their properties; 4.3 Sufficient statistics; 4.4 Hypothesis testing; 4.4.1 Simple hypothesis versus simple alternative; 4.4.2 Composite hypotheses; 4.5 Summary; 5 Real Line-Probability; 5.1 One-dimensional real distributions; 5.2 Joint random variables; 5.3 Differentiable distributions; 5.4 Summary; 6 Continuous Distributions 327 $a6.1 The normal distribution6.1.1 The univariate and bivariate normal distributions; 6.1.2 The multivariate normal distribution; 6.2 Limit theorems; 6.2.1 Convergence concepts; 6.2.2 An inversion formula; 6.3 Gamma and beta distributions; 6.4 The ?2 and related distributions; 6.5 Computer simulations; 6.6 Summary; 7 Parameter Estimation; 7.1 Bias, consistency, and efficiency; 7.2 Normal inference; 7.3 Sums of squares; 7.4 Analysis of variance; 7.5 Linear regression; 7.6 Summary; A Analytical Tools; A.1 Sets and functions; A.2 Limits; A.3 Structure of the real numbers 327 $aA.4 Riemann-Stieltjes integralsA.5 Permutations and determinants; B Statistical Tables; Bibliography; Index 330 $aComprehensive and thorough development of both probability and statistics for serious computer scientists; goal-oriented: ""to present the mathematical analysis underlying probability results""Special emphases on simulation and discrete decision theoryMathematically-rich, but self-contained text, at a gentle paceReview of calculus and linear algebra in an appendixMathematical interludes (in each chapter) which examine mathematical techniques in the context of probabilistic or statistical importanceNumerous section exercises, summaries, historical notes, and Further Readings 606 $aComputer science$xMathematics 606 $aProbabilities 606 $aMathematical statistics$xData processing 615 0$aComputer science$xMathematics. 615 0$aProbabilities. 615 0$aMathematical statistics$xData processing. 676 $a519.2024004 700 $aJohnson$b James L$g(James Lee),$f1942-$017082 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910877699503321 996 $aProbability and statistics for computer science$91575859 997 $aUNINA