This clear exposition begins with basic concepts and moves on to combination of events, dependent events and random variables, Bernoulli trials and the De Moivre-Laplace theorem, a detailed treatment of Markov chains, continuous Markov processes, and more. Includes 150 problems, many with answers. In... read more
Customers who bought this book also bought:
Our Editors also recommend:
An Introduction to Mathematical Modeling by Edward A. Bender Accessible text features over 100 reality-based examples pulled from the science, engineering and operations research fields. Prerequisites: ordinary differential equations, continuous probability. Numerous references. Includes 27 black-and-white figures. 1978 edition.
Information Theory by Robert B. Ash Analysis of channel models and proof of coding theorems; study of specific coding systems; and study of statistical properties of information sources. Sixty problems, with solutions. Advanced undergraduate to graduate level.
An Introduction to Information Theory by Fazlollah M. Reza Graduate-level study for engineering students presents elements of modern probability theory, information theory, coding theory, more. Emphasis on sample space, random variables, capacity, etc. Many reference tables and extensive bibliography. 1961 edition.
Introduction to the Theory of Random Processes by I. I. Gikhman, A. V. Skorokhod Rigorous exposition suitable for elementary instruction. Covers measure theory, axiomatization of probability theory, processes with independent increments, Markov processes and limit theorems for random processes, more. Introduction. Bibliography. 1969 edition.
Elements of the Theory of Markov Processes and Their Applications by A. T. Bharucha-Reid Graduate-level text and reference in probability, with numerous scientific applications. Nonmeasure-theoretic introduction to theory of Markov processes and to mathematical models based on the theory. Appendixes. Bibliographies. 1960 edition.
Basic Probability Theory by Robert B. Ash This text emphasizes the probabilistic way of thinking, rather than by measuring theoretic concepts. Geared toward advanced undergraduates and graduate students, it features solutions to some of the problems. 1970 edition.
Outline of Basic Statistics: Dictionary and Formulas by John E. Freund, Frank J. Williams Handy guide includes a 70-page outline of essential statistical formulas covering grouped and ungrouped data, finite populations, probability, and more, plus over 1,000 clear, concise definitions of statistical terms. 1966 edition.
Good Thinking: The Foundations of Probability and Its Applications by Irving John Good This in-depth treatment of probability theory by a famous British statistician explores Keynesian principles and surveys such topics as Bayesian rationality, corroboration, hypothesis testing, and mathematical tools for induction and simplicity. 1983 edition.
Foundations of Probability by Alfred Renyi Taking an innovative approach to both content and methods, this book explores the foundations, basic concepts, and fundamental results of probability theory, plus mathematical notions of experiments and independence. 1970 edition.
Finite Markov Processes and Their Applications by Marius Iosifescu Self-contained treatment covers both theory and applications. Topics include the fundamental role of homogeneous infinite Markov chains in the mathematical modeling of psychology and genetics. 1980 edition.
Probability Theory by Alfred Renyi This introductory text features problems and exercises illustrating algebras of events, discrete random variables, characteristic functions, and limit theorems. An extensive appendix introduces information theory. 1970 edition.
Theory of Markov Processes by E. B. Dynkin, D. E. Brown, T. Kovary An investigation of the logical foundations of the theory behind Markov random processes, this text explores subprocesses, transition functions, and conditions for boundedness and continuity. 1961 edition.
Introduction to Probability by John E. Freund Featured topics include permutations and factorials, probabilities and odds, frequency interpretation, mathematical expectation, decision making, postulates of probability, rule of elimination, much more. Exercises with some solutions. Summary. 1973 edition.
Games and Decisions: Introduction and Critical Survey by R. Duncan Luce, Howard Raiffa Superb non-technical introduction to game theory, primarily applied to social sciences. Clear, comprehensive coverage of utility theory, 2-person zero-sum games, 2-person non-zero-sum games, n-person games, individual and group decision-making, more. Bibliography.
Principles of Statistics by M. G. Bulmer Concise description of classical statistics, from basic dice probabilities to modern regression analysis. Equal stress on theory and applications. Moderate difficulty; only basic calculus required. Includes problems with answers.
This clear exposition begins with basic concepts and moves on to combination of events, dependent events and random variables, Bernoulli trials and the De Moivre-Laplace theorem, a detailed treatment of Markov chains, continuous Markov processes, and more. Includes 150 problems, many with answers. Indispensable to mathematicians and natural scientists alike.
Reprint of Introductory Probability Theory, 1969 edition.
This book was printed in the United States of America.
Dover books are made to last a lifetime. Our US book-manufacturing partners produce the highest quality books in the world and they create jobs for our fellow citizens. Manufacturing in the United States also ensures that our books are printed in an environmentally friendly fashion, on paper sourced from responsibly managed forests.