A guide to probability theory and application

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Hauptverfasser: Derman, Cyrus 1925-2011 (VerfasserIn), Gleser, Leon Jay (VerfasserIn), Olkin, Ingram 1924-2016 (VerfasserIn)
Format: Buch
Sprache:English
Veröffentlicht: New York Holt, Rinehart and Winston 1973
Schriftenreihe:International series in decision processes.
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Datensatz im Suchindex

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adam_text CONTENTS Preface ix PART I FUNDAMENTAL CONCEPTS 1 Introduction 3 1 History, 3 2 Models, 5 3 The Empirical Basis of Probability Theory, 8 4 Notes and References, 15 2 The Elements of Probability Theory 25 1 Preliminaries, 25 2 Formal Structure: Outcomes and Event Sets, 25 Equality of Event Sets, 28 Inclusion of Event Sets, 29 The Union of Event Sets, 30 The Intersection of Event Sets, 31 The Complement of an Event Set, 31 Mutually Exclusive Event Sets, 34 Some Useful Rules, 35 The Correspondence between the Probability Model and Random Experi¬ ments, 38 3 Formal Structure: Probabilities, 40 4 The Probability Calculus, 42 Law of Inclusion, 42 Law of Complementation, 43 Law of Addition, 45 xi xii CONTENTS 5 Fitting a Probability Model. 51 6 Notes and References, 54 3 Further Concepts of Probability Theory 65 1 Finite Probability Models, 66 2 Simple Random Sampling, 69 3 Composite Random Experiments, 72 A Comment on Notation, 74 4 Conditional Probability, 79 The Probability Calculus for Conditional Probabilities, 83 Law of Multiplication, 86 Law of Multiplication for Nested Events, 89 Partitions. 93 Bayes Rule, 95 5 Independence, 97 6 Appendix: Combinatorial Analysis, 100 Orderings and Permutations, 100 Orderings with Similar Elements, 101 Ordering of r Items from n, 104 Counting of Sets of Items, 105 7 Notes and References, 108 4 Random Variables 125 1 Random Variables, 125 2 Discrete and Continuous Random Variables, 130 3 Cumulative Distribution Functions, 133 Estimating the Cumulative Distribution Function from Data, 143 Mixed Discrete and Continuous Variables and their Cumulative Distribution Functions, 144 4 Probability Mass Functions of Discrete Random Variables, 146 Estimating a Probability Mass Function: Bar Graphs, 149 5 Density Functions, 150 * Rectangular Probability Approximations, 153 Empirical Distributions: Histograms, 160 5 Descriptive Properties of Distributions 175 1 Introduction, 175 2 Measures of Location for a Distribution: The Expected Value, 177 The Expected Value of a Discrete Random Variable, 177 *The Expected Value of a Discrete Random Variable Having an Infinite N umber of Possible Values, 185 The Expected Value of a Continuous Random Variable, 186 *Useof the Rectangular Method of Approximation, 188 The Expected Value as a Measure of Location, 191 Notation and Terminology, 193 3 Other Measures of Location for a Distribution: Median, Quantile, Mode, 193 CONTENTS xiii Medians, 193 Quantiles, 197 Modes, 203 Choice of a Measure of Location, 205 4 Measures of Dispersion for a Distribution: The Variance, 210 5 Higher Moments, 217 6 Inequalities for Probabilities, 223 Proof of the Markov Inequality, 224 Use of the Markov Inequality, 225 Supplementary Reading, 231 7 Appendix, 233 PART II PROBABILITY MODELS 6 Special Distributions: Discrete Case 247 1 Bernoulli and Binomial Distributions, 247 Bernoulli Distribution, 248 Binomial Distribution, 249 Tables, 255 2 Hypergeometric Distribution, 256 Derivation of the Hypergeometric Distribution, 258 Approximation of the Hypergeometric Distribution by the Binomial Distri¬ bution, 262 Uses of the Hypergeometric Distribution, 262 Description of Tables, 264 3 Poisson Distribution, 265 A Method for Fitting the Poisson Distribution, 266 Applications of the Poisson Distribution, 269 The Poisson Distribution as an Approximation of the Binomial Distribution, 272 Tables of the Poisson Distribution, 273 4 Geometric Distribution, 274 A Method for Fitting the Geometric Distribution, 277 Description of Tables of the Geometric Distribution, 279 Notes and References. 279 5 Negative Binomial Distribution, 280 *Generalization of the Negative Binomial Distribution, 284 * A Method for Fitting the Negative Binomial Distribution, 287 Applications of the Negative Binomial Distribution. 290 Description of Tables of the Negative Binomial Distribution, 292 6 Discrete Uniform Distribution, 293 Lotteries, 294 Generalized Discrete Uniform Distribution. 295 7 *Other Discrete Distributions, 296 The Zeta Distribution, 296 The Truncated Poisson Distribution. 299 References to Other Discrete Distributions, 304 8 Summary of Discrete Distribution, 304 xiv CONTENTS 7 The Normal Distribution 324 1 Introduction, 324 History, 326 2 Probability Calculations for the Normal Distributions, 332 Tail Probabilities, 336 Probabilities of Intervals of Numbers, 339 3 Fitting a Normal Distribution, 341 4 The Central Limit Theorem, 345 * A Justification of the Normal Distribution by the Central Limit Theorem, 349 8 Special Distributions: Continuous Case 358 1 The Exponential Distribution, 359 Fitting the Exponential Distribution to Data, 361 Probability Calculations, 364 The Survival Function, 365 An Interesting Property of the Exponential Distribution, 367 Notes and References, 368 2 The Gamma Distribution, 369 The Standard Gamma Density Function, 370 Fitting the Gamma Distribution to Data, 372 Probability Calculations, 374 3 *The Weibull Distribution, 378 A Theoretical Explanation, 385 Fitting the Weibull Distribution to Data, 385 The Survival Function, 389 4 The Uniform Distribution, 391 Probability Calculations, 393 Applications, 396 5 *The Beta Distribution, 398 Fitting the Beta Distribution to Data, 404 Probability Calculations, 405 Notes and References, 409 6 * Other Continuous Distributions, 410 The Lognormal Distribution, 410 The Cauchy Distribution, 414 Notes and References, 418 9 Multivariate Distributions 432 1 Introduction, 432 2 Discrete Bivariate Distributions, 433 Marginal Distributions, 439 Example of the Construction of a Bivariate Probability Model, 443 Conditional Distributions, 446 The Regression Function, 450 3 Descriptive Properties of Bivariate Distribution, 453 Rescaling Techniques, 460 The Correlation Coefficient, 464 CONTENTS xv Correlation and Statistical Independence, 469 Correlation and Statistical Dependence, 472 4 Continuous Bivariate Distributions, 475 Marginal Probability Density Functions, 479 Conditional Probability Density Functions, 482 Statistical Independence, 483 Descriptive Properties of Bivariate Continuous Distributions, 484 5 The Bivariate Normal Distribution, 486 The Probability Contours of a Bivariate Normal Distribution, 490 The Standard Bivariate Normal Distribution, 493 6 *Some Multivariate Generalizations: Trivariate Discrete Distributions, 501 Conditional Distributions and Partial Correlation Coefficients, 506 Statistical Independence, 508 The Multinomial Distribution, 509 10 Weighted Sum of Random Variables 519 1 Standardization of Random Variables, 519 2 Weighted Sums of Random Variables, 523 Some Special Cases, 526 Expected Values and Variances, 527 3 The Law of Large Numbers, 530 4 Further Comments on the Central Limit Theorem, 533 The Continuity Correction, 539 5 *Appendix: Moment Generating Functions, 541 11 Markov Chains 550 1 Introduction, 550 2 Markov Chains, 552 3 Applications, 559 An Example from Psychology, 559 Social Processes, 563 Genetics, 566 4 Calculation of Step Transition Probabilities, 571 2 Step Transition Probabilities, 572 3 Step Transition Probabilities, 578 General it Step Transition Probabilities, 582 An Alternative Method for Calculating £ Step Transition Probabilities, 587 5 Absolute or Unconditional Probabilities, 588 12 * Markov Chains II: First Passage Times, Recurrent States, and Long Run Probabilities 597 1 First Passage Times, 597 Calculation of the Probability Distribution of the First Passage Time K,,, 600 Infinite First Passage Times, 611 2 Recurrent and Transient States, 615 xvi CONTENTS 3 Expected First Passage Times, 620 Alternate Computation for Expected First Passage Times, 623 4 Probabilistic Equilibrium of a Markov Chain, 630 5 Classes of States, 634 Classes of Communicating States, 636 6 Aperiodic, Irreducible Markov Chains, 640 Periodic States and Periodic Chains, 642 Aperiodic States, 644 Steady State Equations, 648 7 Absorbing Markov Chains, 651 8 Notes and References, 657 Bibliography 663 Tables 671 Answers 717 Name Index 743 Subject Index 745
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author Derman, Cyrus 1925-2011
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spelling Derman, Cyrus 1925-2011 Verfasser (DE-588)170709280 aut
A guide to probability theory and application Cyrus Derman ; Leon J. Gleser ; Ingram Olkin
New York Holt, Rinehart and Winston 1973
XVI,750 S.
txt rdacontent
n rdamedia
nc rdacarrier
International series in decision processes.
Probabilités
Probabilities
Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd rswk-swf
Wahrscheinlichkeitsrechnung (DE-588)4064324-4 s
DE-604
Gleser, Leon Jay Verfasser aut
Olkin, Ingram 1924-2016 Verfasser (DE-588)118889036 aut
HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=001962175&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle Derman, Cyrus 1925-2011
Gleser, Leon Jay
Olkin, Ingram 1924-2016
A guide to probability theory and application
Probabilités
Probabilities
Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd
subject_GND (DE-588)4064324-4
title A guide to probability theory and application
title_auth A guide to probability theory and application
title_exact_search A guide to probability theory and application
title_full A guide to probability theory and application Cyrus Derman ; Leon J. Gleser ; Ingram Olkin
title_fullStr A guide to probability theory and application Cyrus Derman ; Leon J. Gleser ; Ingram Olkin
title_full_unstemmed A guide to probability theory and application Cyrus Derman ; Leon J. Gleser ; Ingram Olkin
title_short A guide to probability theory and application
title_sort a guide to probability theory and application
topic Probabilités
Probabilities
Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd
topic_facet Probabilités
Probabilities
Wahrscheinlichkeitsrechnung
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