Well known for the clear, inductive nature of its exposition, this reprint volume is an excellent introduction to mathematical probability theory. It may be used as a graduate-level text in one- or two-semester courses in probability for students who are familiar with basic measure theory, or as a supplement in courses in stochastic processes or mathematical statistics. Designed around the needs of the student, this book achieves readability and clarity by giving the most important results in each area while not dwelling on any one subject. Each new idea or concept is introduced from an intuitive, common-sense point of view. Students are helped to understand why things work, instead of being given a dry theorem-proof regime.
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'This excellent textbook by L. Breiman, which was used by many people to learn probability and which was out of print for some years, is again available as an unchanged republication. It gives an introduction to probability based on measure theory.' F. Hofbauer, Monatschefte für Mathematik
'A reprint of the 1986 Addison-Wesley text, long out of print (TR, October 1968). This is one of the true classics in the field of probability and its reappearance is welcome. At this price it belongs on the shelf of every student and professional in the area.' American Mathematical Monthly
'The style of writing is very informal and chatty. With a few exceptions this goes over quite well. Though one might reproach the author with an undue haste in keeping the reader's attention, and in skimming the cream of many subjects, the overall effect is good and may to some extent alleviate the discouragement of many non-specialists who want a reasonably modern account not overly encumbered with heavy analytic and set-theoretic preliminaries.' D. A. Darling, Mathematical Reviews
'This book is written on an advanced graduate level and addresses statisticians, engineers, and mathematicians who are interested in probability theory and measure and function theory.' Ion A. Craciun, Recenzii
'A reprint of the 1986 Addison-Wesley text, long out of print (TR, October 1968). This is one of the true classics in the field of probability and its reappearance is welcome. At this price it belongs on the shelf of every student and professional in the area.' American Mathematical Monthly
'The style of writing is very informal and chatty. With a few exceptions this goes over quite well. Though one might reproach the author with an undue haste in keeping the reader's attention, and in skimming the cream of many subjects, the overall effect is good and may to some extent alleviate the discouragement of many non-specialists who want a reasonably modern account not overly encumbered with heavy analytic and set-theoretic preliminaries.' D. A. Darling, Mathematical Reviews
'This book is written on an advanced graduate level and addresses statisticians, engineers, and mathematicians who are interested in probability theory and measure and function theory.' Ion A. Craciun, Recenzii
Book Description
This reprint volume is an excellent introduction to mathematical probability theory, suitable for graduate-level use in probability courses or as a supplement for courses in stochastic processes or mathematical statistics. The readability and clarity of the style help students understand why things work, instead of handing them a theorem-proof regime.
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Inside This Book
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First Sentence:
A good deal of probability theory consists of the study of limit theorems. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
coordinate representation process, random signs problem, stationary initial distribution, strong limit theorems, infinitesimal conditions, regular conditional distribution, pure jump process, bounded convergence theorem, local limit theorem, central limit problem, regular conditional probability, infinitely divisible laws, stationary transition probabilities, joint normal distribution, optional sampling theorem, mass preserving, renewal theorem, invariant event, stationary point process, random boundaries, exit distributions, first exit time, successive sums, divisible distribution, independent increments Key Phrases - Capitalized Phrases (CAPs): (learn more)
Charles Stone, David Freedman, Use the Taylor New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
A good deal of probability theory consists of the study of limit theorems. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
coordinate representation process, random signs problem, stationary initial distribution, strong limit theorems, infinitesimal conditions, regular conditional distribution, pure jump process, bounded convergence theorem, local limit theorem, central limit problem, regular conditional probability, infinitely divisible laws, stationary transition probabilities, joint normal distribution, optional sampling theorem, mass preserving, renewal theorem, invariant event, stationary point process, random boundaries, exit distributions, first exit time, successive sums, divisible distribution, independent increments Key Phrases - Capitalized Phrases (CAPs): (learn more)
Charles Stone, David Freedman, Use the Taylor New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 51
books:
See all 51 books this book cites
- Measure Theory (Graduate Texts in Mathematics) (v. 18) by Paul R. Halmos in Front Matter, and Back Matter
- Differential Equations by HABERMAN in Front Matter
- Introduction to Invariant Imbedding (Pure & Applied Mathematics Monograph) by Richard Bellman in Front Matter
- An Introduction to the Theory of Stationary Random Functions (Dover Phoenix Editions) by A. M. Yaglom in Back Matter
- Mathematical Theory of Reliability (Classics in Applied Mathematics) by Richard E. Barlow in Front Matter
See all 51 books this book cites
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