Author | Capiล{132}ski, Marek. author |
---|---|

Title | Probability Through Problems [electronic resource] / by Marek Capiล{132}ski, Tomasz Zastawniak |

Imprint | New York, NY : Springer New York : Imprint: Springer, 2001 |

Connect to | http://dx.doi.org/10.1007/978-0-387-21659-1 |

Descript | VIII, 260 p. online resource |

SUMMARY

This book of problems has been designed to accompany an undergraduate course in probability. It will also be useful for students with interest in probability who wish to study on their own. The only prerequisite is basic algebra and calculus. This includes some elementary experience in set theory, sequences and series, functions of one variable, and their derivatives. Familiarity with integrals would be a bonus. A brief survey of terminology and notation in set theory and calculus is provided. Each chapter is divided into three parts: Problems, Hints, and Solutions. To make the book reasonably self-contained, all problem sections include expository material. Definitions and statements of important results are interlaced with relevant problems. The latter have been selected to motivate abstract definitions by concrete examples and to lead in manageable steps toward general results, as well as to provide exercises based on the issues and techniques introduced in each chapter. The hint sections are an important part of the book, designed to guide the reader in an informal manner. This makes Probability Through Probยญ lems particularly useful for self-study and can also be of help in tutorials. Those who seek mathematical precision will find it in the worked solutions provided. However, students are strongly advised to consult the hints prior to looking at the solutions, and, first of all, to try to solve each problem on their own

CONTENT

Terminology and Notation -- 1 Modeling Random Experiments -- 2 Classical Probability Spaces -- 3 Fields -- 4 Finitely Additive Probability -- 5 Sigma Fields -- 6 Countably Additive Probability -- 7 Conditional Probability and Independence -- 8 Random Variables and Their Distributions -- 9 Expectation and Variance -- 10 Conditional Expectation -- 11 Characteristic Functions -- 12 Limit Theorems

Mathematics
Probabilities
Mathematics
Probability Theory and Stochastic Processes