One thousand exercises in probability:
This volume of more than 1300 exercises and solutions in probability theory has two roles. It is both a freestanding book of exercises and solutions in probability theory, and a manual for students and teachers covering the exercises and problems in the companion volume Probability Theory and Random...
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| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Oxford, United Kingdom
Oxford University Press
2020
|
| Edition: | Third edition |
| Subjects: | |
| Online Access: | FHD01 TUM01 |
| Summary: | This volume of more than 1300 exercises and solutions in probability theory has two roles. It is both a freestanding book of exercises and solutions in probability theory, and a manual for students and teachers covering the exercises and problems in the companion volume Probability Theory and Random Processes, 4e |
| Physical Description: | 1 Online-Ressource (xii, 580 Seiten) |
| ISBN: | 9780192586872 |
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| 264 | 1 | |a Oxford, United Kingdom |b Oxford University Press |c 2020 | |
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| 505 | 8 | |a Cover -- One Thousand Exercises in Probability -- Copyright -- Epigraph -- Preface to the Third Edition -- Contents -- Questions -- 1 Events and their probabilities -- 1.2 Exercises. Events as sets -- 1.3 Exercises. Probability -- 1.4 Exercises. Conditional probability -- 1.5 Exercises. Independence -- 1.7 Exercises. Worked examples -- 1.8 Problems -- 2 Random variables and their distributions -- 2.1 Exercises. Random variables -- 2.2 Exercises. The law of averages -- 2.3 Exercises. Discrete and continuous variables -- 2.4 Exercises. Worked examples -- 2.5 Exercises. Random vectors | |
| 505 | 8 | |a 2.7 Problems -- 3 Discrete random variables -- 3.1 Exercises. Probability mass functions -- 3.2 Exercises. Independence -- 3.3 Exercises. Expectation -- 3.4 Exercises. Indicators and matching -- 3.5 Exercises. Examples of discrete variables -- 3.6 Exercises. Dependence -- 3.7 Exercises. Conditional distributions and conditional expectation -- 3.8 Exercises. Sums of random variables -- 3.9 Exercises. Simple random walk -- 3.10 Exercises. Random walk: counting sample paths -- 3.11 Problems -- 4 Continuous random variables -- 4.1 Exercises. Probability density functions | |
| 505 | 8 | |a 4.2 Exercises. Independence -- 4.3 Exercises. Expectation -- 4.4 Exercises. Examples of continuous variables -- 4.5 Exercises. Dependence -- 4.6 Exercises. Conditional distributions and conditional expectation -- 4.7 Exercises. Functions of random variables -- 4.8 Exercises. Sums of random variables -- 4.9 Exercises. Multivariate normal distribution -- 4.10 Exercises. Distributions arising from the normal distribution -- 4.11 Exercises. Sampling from a distribution -- 4.12 Exercises. Coupling and Poisson approximation -- 4.13 Exercises. Geometrical probability -- 4.14 Problems | |
| 505 | 8 | |a 5 Generating functions and their applications -- 5.1 Exercises. Generating functions -- 5.2 Exercises. Some applications -- 5.3 Exercises. Random walk -- 5.4 Exercises. Branching processes -- 5.5 Exercises. Age-dependent branching processes -- 5.6 Exercises. Expectation revisited -- 5.7 Exercises. Characteristic functions -- 5.8 Exercises. Examples of characteristic functions -- 5.9 Exercises. Inversion and continuity theorems -- 5.10 Exercises. Two limit theorems -- 5.11 Exercises. Large deviations -- 5.12 Problems -- 6 Markov chains -- 6.1 Exercises. Markov processes | |
| 505 | 8 | |a 6.2 Exercises. Classification of states -- 6.3 Exercises. Classification of chains -- 6.4 Exercises. Stationary distributions and the limit theorem -- 6.5 Exercises. Reversibility -- 6.6 Exercises. Chains with finitely many states -- 6.7 Exercises. Branching processes revisited -- 6.8 Exercises. Birth processes and the Poisson process -- 6.9 Exercises. Continuous-time Markov chains -- 6.10 Exercises. Kolmogorov equations and the limit theorem -- 6.11 Exercises. Birth-death processes and imbedding -- 6.12 Exercises. Special processes -- 6.13 Exercises. Spatial Poisson processes | |
| 505 | 8 | |a 6.14 Exercises. Markov chain Monte Carlo | |
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| contents | Cover -- One Thousand Exercises in Probability -- Copyright -- Epigraph -- Preface to the Third Edition -- Contents -- Questions -- 1 Events and their probabilities -- 1.2 Exercises. Events as sets -- 1.3 Exercises. Probability -- 1.4 Exercises. Conditional probability -- 1.5 Exercises. Independence -- 1.7 Exercises. Worked examples -- 1.8 Problems -- 2 Random variables and their distributions -- 2.1 Exercises. Random variables -- 2.2 Exercises. The law of averages -- 2.3 Exercises. Discrete and continuous variables -- 2.4 Exercises. Worked examples -- 2.5 Exercises. Random vectors 2.7 Problems -- 3 Discrete random variables -- 3.1 Exercises. Probability mass functions -- 3.2 Exercises. Independence -- 3.3 Exercises. Expectation -- 3.4 Exercises. Indicators and matching -- 3.5 Exercises. Examples of discrete variables -- 3.6 Exercises. Dependence -- 3.7 Exercises. Conditional distributions and conditional expectation -- 3.8 Exercises. Sums of random variables -- 3.9 Exercises. Simple random walk -- 3.10 Exercises. Random walk: counting sample paths -- 3.11 Problems -- 4 Continuous random variables -- 4.1 Exercises. Probability density functions 4.2 Exercises. Independence -- 4.3 Exercises. Expectation -- 4.4 Exercises. Examples of continuous variables -- 4.5 Exercises. Dependence -- 4.6 Exercises. Conditional distributions and conditional expectation -- 4.7 Exercises. Functions of random variables -- 4.8 Exercises. Sums of random variables -- 4.9 Exercises. Multivariate normal distribution -- 4.10 Exercises. Distributions arising from the normal distribution -- 4.11 Exercises. Sampling from a distribution -- 4.12 Exercises. Coupling and Poisson approximation -- 4.13 Exercises. Geometrical probability -- 4.14 Problems 5 Generating functions and their applications -- 5.1 Exercises. Generating functions -- 5.2 Exercises. Some applications -- 5.3 Exercises. Random walk -- 5.4 Exercises. Branching processes -- 5.5 Exercises. Age-dependent branching processes -- 5.6 Exercises. Expectation revisited -- 5.7 Exercises. Characteristic functions -- 5.8 Exercises. Examples of characteristic functions -- 5.9 Exercises. Inversion and continuity theorems -- 5.10 Exercises. Two limit theorems -- 5.11 Exercises. Large deviations -- 5.12 Problems -- 6 Markov chains -- 6.1 Exercises. Markov processes 6.2 Exercises. Classification of states -- 6.3 Exercises. Classification of chains -- 6.4 Exercises. Stationary distributions and the limit theorem -- 6.5 Exercises. Reversibility -- 6.6 Exercises. Chains with finitely many states -- 6.7 Exercises. Branching processes revisited -- 6.8 Exercises. Birth processes and the Poisson process -- 6.9 Exercises. Continuous-time Markov chains -- 6.10 Exercises. Kolmogorov equations and the limit theorem -- 6.11 Exercises. Birth-death processes and imbedding -- 6.12 Exercises. Special processes -- 6.13 Exercises. Spatial Poisson processes 6.14 Exercises. Markov chain Monte Carlo |
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| discipline | Mathematik |
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| spelling | Grimmett, Geoffrey 1950- Verfasser (DE-588)120872919 aut One thousand exercises in probability Geoffrey R. Grimmett and David R. Stirzaker Third edition Oxford, United Kingdom Oxford University Press 2020 1 Online-Ressource (xii, 580 Seiten) txt rdacontent c rdamedia cr rdacarrier Cover -- One Thousand Exercises in Probability -- Copyright -- Epigraph -- Preface to the Third Edition -- Contents -- Questions -- 1 Events and their probabilities -- 1.2 Exercises. Events as sets -- 1.3 Exercises. Probability -- 1.4 Exercises. Conditional probability -- 1.5 Exercises. Independence -- 1.7 Exercises. Worked examples -- 1.8 Problems -- 2 Random variables and their distributions -- 2.1 Exercises. Random variables -- 2.2 Exercises. The law of averages -- 2.3 Exercises. Discrete and continuous variables -- 2.4 Exercises. Worked examples -- 2.5 Exercises. Random vectors 2.7 Problems -- 3 Discrete random variables -- 3.1 Exercises. Probability mass functions -- 3.2 Exercises. Independence -- 3.3 Exercises. Expectation -- 3.4 Exercises. Indicators and matching -- 3.5 Exercises. Examples of discrete variables -- 3.6 Exercises. Dependence -- 3.7 Exercises. Conditional distributions and conditional expectation -- 3.8 Exercises. Sums of random variables -- 3.9 Exercises. Simple random walk -- 3.10 Exercises. Random walk: counting sample paths -- 3.11 Problems -- 4 Continuous random variables -- 4.1 Exercises. Probability density functions 4.2 Exercises. Independence -- 4.3 Exercises. Expectation -- 4.4 Exercises. Examples of continuous variables -- 4.5 Exercises. Dependence -- 4.6 Exercises. Conditional distributions and conditional expectation -- 4.7 Exercises. Functions of random variables -- 4.8 Exercises. Sums of random variables -- 4.9 Exercises. Multivariate normal distribution -- 4.10 Exercises. Distributions arising from the normal distribution -- 4.11 Exercises. Sampling from a distribution -- 4.12 Exercises. Coupling and Poisson approximation -- 4.13 Exercises. Geometrical probability -- 4.14 Problems 5 Generating functions and their applications -- 5.1 Exercises. Generating functions -- 5.2 Exercises. Some applications -- 5.3 Exercises. Random walk -- 5.4 Exercises. Branching processes -- 5.5 Exercises. Age-dependent branching processes -- 5.6 Exercises. Expectation revisited -- 5.7 Exercises. Characteristic functions -- 5.8 Exercises. Examples of characteristic functions -- 5.9 Exercises. Inversion and continuity theorems -- 5.10 Exercises. Two limit theorems -- 5.11 Exercises. Large deviations -- 5.12 Problems -- 6 Markov chains -- 6.1 Exercises. Markov processes 6.2 Exercises. Classification of states -- 6.3 Exercises. Classification of chains -- 6.4 Exercises. Stationary distributions and the limit theorem -- 6.5 Exercises. Reversibility -- 6.6 Exercises. Chains with finitely many states -- 6.7 Exercises. Branching processes revisited -- 6.8 Exercises. Birth processes and the Poisson process -- 6.9 Exercises. Continuous-time Markov chains -- 6.10 Exercises. Kolmogorov equations and the limit theorem -- 6.11 Exercises. Birth-death processes and imbedding -- 6.12 Exercises. Special processes -- 6.13 Exercises. Spatial Poisson processes 6.14 Exercises. Markov chain Monte Carlo This volume of more than 1300 exercises and solutions in probability theory has two roles. It is both a freestanding book of exercises and solutions in probability theory, and a manual for students and teachers covering the exercises and problems in the companion volume Probability Theory and Random Processes, 4e Probabilities / Problems, exercises, etc Stochastic processes / Problems, exercises, etc Probabilities fast Stochastic processes fast Wahrscheinlichkeitstheorie (DE-588)4079013-7 gnd rswk-swf (DE-588)4143389-0 Aufgabensammlung gnd-content Wahrscheinlichkeitstheorie (DE-588)4079013-7 s DE-604 Stirzaker, David Verfasser (DE-588)1158150989 aut Erscheint auch als Druck-Ausgabe 978-0-19-884761-8 |
| spellingShingle | Grimmett, Geoffrey 1950- Stirzaker, David One thousand exercises in probability Cover -- One Thousand Exercises in Probability -- Copyright -- Epigraph -- Preface to the Third Edition -- Contents -- Questions -- 1 Events and their probabilities -- 1.2 Exercises. Events as sets -- 1.3 Exercises. Probability -- 1.4 Exercises. Conditional probability -- 1.5 Exercises. Independence -- 1.7 Exercises. Worked examples -- 1.8 Problems -- 2 Random variables and their distributions -- 2.1 Exercises. Random variables -- 2.2 Exercises. The law of averages -- 2.3 Exercises. Discrete and continuous variables -- 2.4 Exercises. Worked examples -- 2.5 Exercises. Random vectors 2.7 Problems -- 3 Discrete random variables -- 3.1 Exercises. Probability mass functions -- 3.2 Exercises. Independence -- 3.3 Exercises. Expectation -- 3.4 Exercises. Indicators and matching -- 3.5 Exercises. Examples of discrete variables -- 3.6 Exercises. Dependence -- 3.7 Exercises. Conditional distributions and conditional expectation -- 3.8 Exercises. Sums of random variables -- 3.9 Exercises. Simple random walk -- 3.10 Exercises. Random walk: counting sample paths -- 3.11 Problems -- 4 Continuous random variables -- 4.1 Exercises. Probability density functions 4.2 Exercises. Independence -- 4.3 Exercises. Expectation -- 4.4 Exercises. Examples of continuous variables -- 4.5 Exercises. Dependence -- 4.6 Exercises. Conditional distributions and conditional expectation -- 4.7 Exercises. Functions of random variables -- 4.8 Exercises. Sums of random variables -- 4.9 Exercises. Multivariate normal distribution -- 4.10 Exercises. Distributions arising from the normal distribution -- 4.11 Exercises. Sampling from a distribution -- 4.12 Exercises. Coupling and Poisson approximation -- 4.13 Exercises. Geometrical probability -- 4.14 Problems 5 Generating functions and their applications -- 5.1 Exercises. Generating functions -- 5.2 Exercises. Some applications -- 5.3 Exercises. Random walk -- 5.4 Exercises. Branching processes -- 5.5 Exercises. Age-dependent branching processes -- 5.6 Exercises. Expectation revisited -- 5.7 Exercises. Characteristic functions -- 5.8 Exercises. Examples of characteristic functions -- 5.9 Exercises. Inversion and continuity theorems -- 5.10 Exercises. Two limit theorems -- 5.11 Exercises. Large deviations -- 5.12 Problems -- 6 Markov chains -- 6.1 Exercises. Markov processes 6.2 Exercises. Classification of states -- 6.3 Exercises. Classification of chains -- 6.4 Exercises. Stationary distributions and the limit theorem -- 6.5 Exercises. Reversibility -- 6.6 Exercises. Chains with finitely many states -- 6.7 Exercises. Branching processes revisited -- 6.8 Exercises. Birth processes and the Poisson process -- 6.9 Exercises. Continuous-time Markov chains -- 6.10 Exercises. Kolmogorov equations and the limit theorem -- 6.11 Exercises. Birth-death processes and imbedding -- 6.12 Exercises. Special processes -- 6.13 Exercises. Spatial Poisson processes 6.14 Exercises. Markov chain Monte Carlo Probabilities / Problems, exercises, etc Stochastic processes / Problems, exercises, etc Probabilities fast Stochastic processes fast Wahrscheinlichkeitstheorie (DE-588)4079013-7 gnd |
| subject_GND | (DE-588)4079013-7 (DE-588)4143389-0 |
| title | One thousand exercises in probability |
| title_auth | One thousand exercises in probability |
| title_exact_search | One thousand exercises in probability |
| title_exact_search_txtP | One thousand exercises in probability |
| title_full | One thousand exercises in probability Geoffrey R. Grimmett and David R. Stirzaker |
| title_fullStr | One thousand exercises in probability Geoffrey R. Grimmett and David R. Stirzaker |
| title_full_unstemmed | One thousand exercises in probability Geoffrey R. Grimmett and David R. Stirzaker |
| title_short | One thousand exercises in probability |
| title_sort | one thousand exercises in probability |
| topic | Probabilities / Problems, exercises, etc Stochastic processes / Problems, exercises, etc Probabilities fast Stochastic processes fast Wahrscheinlichkeitstheorie (DE-588)4079013-7 gnd |
| topic_facet | Probabilities / Problems, exercises, etc Stochastic processes / Problems, exercises, etc Probabilities Stochastic processes Wahrscheinlichkeitstheorie Aufgabensammlung |
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