The structure of probability theory with applications

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1. Verfasser: Thomasian, Aram J. (VerfasserIn)
Format: Buch
Sprache:English
Veröffentlicht: New York [u.a.] McGraw-Hill 1969
Schriftenreihe:McGraw-Hill series in probability and statistics
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Datensatz im Suchindex

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adam_text Contents PREFACE vii CHAPTER I SETS I l l Sets 1 1 2 Some set theory terminology 2 1 3 Operations on sets 4 1 4 Set identities 7 CHAPTER 2 COMBINATORICS 11 2 1 Cartesian products 11 2 2 The size of a cartesian product 13 2 3 Binomial coefficients 20 *2 4 The multinomial and hypergeometric formulas 30 CHAPTER 3 FUNCTIONS 36 3 1 Functions 36 3 2 Additional terminology concerning functions 40 3 3 Composition 41 3 4 Inverse images 43 3 5 One to one correspondence 46 CHAPTER 4 COUNTABILITY 49 4 1 Cardinality 49 4 2 Countable sets 50 4 3 An uncountable set 55 CHAPTER 5 ABSOLUTELY CONVERGENT SERIES 60 5 1 Review of series 60 5 2 Absolutely convergent series 62 5 3 Iterated summation 65 xiii CHAPTER 6 DISCRETE PROBABILITY DENSITIES 68 6 1 The random wheel experiment 68 6 2 Discrete probability densities 70 6 3 Relative frequencies 75 6 4 Discrete probability measures 78 CHAPTER 7 INDEPENDENT EVENTS 88 7 1 Conditional probabilities 88 7 2 Bayes theorem 93 7 3 Independence of two events 96 7 4 Independence of n events 99 CHAPTER 8 INDEPENDENT EXPERIMENTS 103 8 1 Independent experiments 103 8 2 The binomial density 107 8 3 The Poisson density 113 8 4 The Pascal density 121 CHAPTER 9 THE MEAN AND VARIANCE 127 9 1 The mean of a density 127 9 2 The variance of a density 131 9 3 A linear transformation of a density 135 9 4 The moment generating function 138 CHAPTER 10 THE LAW OF LARGE NUMBERS FOR BERNOULLI TRIALS 146 10 1 Chebychev s inequality 146 10 2 The law of large numbers for Bernoulli trials 153 *IO 3 The Weierstrass approximation theorem 155 CHAPTER | | RANDOM VARIABLES 161 ll l Random points and random variables 161 M 2 Independent random variables 174 11 3 Expectation 183 IM Correlation and linear prediction 202 xiv CHAPTER 12 THE LAW OF LARGE NUMBERS 212 12 1 The weak law of large numbers 213 12 2 Sampling experiments 219 12 3 The strong law of large numbers 225 *l2 4 The proof of the strong law of large numbers 228 CHAPTER 13 THE CENTRAL LIMIT THEOREM 233 13 1 The normal density 233 13 2 The central limit theorem 239 *l3 3 The normal approximation to the binomial 251 *l3 4 A numerical example 256 CHAPTER 14 CONDITIONAL EXPECTATIONS AND BRANCHING PROCESSES 261 *I4 I Conditional expectation 261 ?14 2 The sum of a random number of random variables 274 ?14 3 Branching processes 286 CHAPTER 15 PROBABILITY SPACES 295 15 1 Probability spaces 295 15 2 Induced distributions 298 15 3 Independence 302 15 4 Expectation 306 *l5 5 Conditional expectation 314 CHAPTER 16 CONTINUOUS PROBABILITY DENSITIES 320 16 1 Continuous probability densities 320 16 2 The density of Y = g(X) 339 16 3 Induced densities, n 2 354 16 4 Independence 366 16 5 Expectation 379 ?16 6 Conditional expectations 395 CHAPTER 17 DISTRIBUTION FUNCTIONS 404 17 1 Distribution functions on R 404 17 2 The distribution function of Y = g(X) 422 17 3 Distribution functions on Rn 434 ?17 4 The method of indicators 440 XV CHAPTER 18 MULTIVARIATE NORMAL DENSITIES AND CHARACTERISTIC FUNCTIONS 447 18 1 Covariance matrices and linear prediction 447 18 2 Multivariate normal densities 457 18 3 Characteristic functions 467 18 4 A vector central limit theorem 479 CHAPTER 19 PROOF OF THE CENTRAL LIMIT THEOREM 483 CHAPTER 20 THE METHOD OF TRUNCATION 494 20 1 The method of truncation and the WLLN 494 20 2 The central limit theorem and truncation 500 20 3 The strong law of large numbers and truncation 505 CHAPTER 21 PROBABILITY SPACES: A RIGOROUS PRESENTATION 513 21 1 Probability spaces 514 21 2 Borel sets 515 21 3 Random variables and independence 519 21 4 Expectation 524 CHAPTER 22 INTRODUCTION TO STOCHASTIC PROCESSES 527 22 1 Introduction 528 22 2 Consistent families, and processes having stationary independent increments 537 22 3 Construction and uniqueness of processes 546 CHAPTER 23 THE POISSON PROCESS AND SOME OF ITS GENERALIZATIONS 556 23 1 Introduction 557 23 2 The uniqueness of the Poisson process 565 23 3 Two characterizations of a Poisson process 570 23 4 Compound Poisson processes 581 23 5 Nonhomogeneous Poisson processes 584 23 6 Pure birth processes 588 23 7 Birth and death processes 596 CHAPTER 24 THE WIENER PROCESS 603 24 1 Introduction 603 24 2 Some simple properties of Wiener processes 609 24 3 Covariance functions and normal processes 623 xvi APPENDIX I SEVERAL FREQUENTLY USED FORMULAS 629 APPENDIX 2 THE SUPREMUM 630 APPENDIX 3 SUMMABILITY 634 SUMMARIES 639 SELECTED ANSWERS AND SOLUTIONS 727 INDEX 741 xvii
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spelling Thomasian, Aram J. Verfasser aut
The structure of probability theory with applications Aram J. Thomasian
New York [u.a.] McGraw-Hill 1969
XVII, 746 S.
txt rdacontent
n rdamedia
nc rdacarrier
McGraw-Hill series in probability and statistics
Probabilidade (Textos Introdutorios) larpcal
Probabilities
Wahrscheinlichkeit (DE-588)4137007-7 gnd rswk-swf
Struktur (DE-588)4058125-1 gnd rswk-swf
Theorie (DE-588)4059787-8 gnd rswk-swf
Wahrscheinlichkeit (DE-588)4137007-7 s
Theorie (DE-588)4059787-8 s
Struktur (DE-588)4058125-1 s
DE-604
HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=001859872&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle Thomasian, Aram J.
The structure of probability theory with applications
Probabilidade (Textos Introdutorios) larpcal
Probabilities
Wahrscheinlichkeit (DE-588)4137007-7 gnd
Struktur (DE-588)4058125-1 gnd
Theorie (DE-588)4059787-8 gnd
subject_GND (DE-588)4137007-7
(DE-588)4058125-1
(DE-588)4059787-8
title The structure of probability theory with applications
title_auth The structure of probability theory with applications
title_exact_search The structure of probability theory with applications
title_full The structure of probability theory with applications Aram J. Thomasian
title_fullStr The structure of probability theory with applications Aram J. Thomasian
title_full_unstemmed The structure of probability theory with applications Aram J. Thomasian
title_short The structure of probability theory with applications
title_sort the structure of probability theory with applications
topic Probabilidade (Textos Introdutorios) larpcal
Probabilities
Wahrscheinlichkeit (DE-588)4137007-7 gnd
Struktur (DE-588)4058125-1 gnd
Theorie (DE-588)4059787-8 gnd
topic_facet Probabilidade (Textos Introdutorios)
Probabilities
Wahrscheinlichkeit
Struktur
Theorie
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