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Recommendations... Probability, Statistics and Truth
by Richard von Mises
This comprehensive study of probability considers the approaches of Pascal, Laplace, Poisson, and others. It also discusses Laws of Large Numbers, the theory of errors, and other relevant topics.
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| |  Experimental Statistics
by Mary Gibbons Natrella
A handbook for those seeking engineering information and quantitative data for designing, developing, constructing, and testing equipment. Covers the planning of experiments, the analyzing of extreme-value data; and more. 1966 edition. Index. Includes 52 figures and 76 tables.
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 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.
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| |  Statistical Inference
by Vijay K. Rohatgi
This treatment of probability and statistics examines discrete and continuous models, functions of random variables and random vectors, large-sample theory, more. Hundreds of problems (some with solutions). 1984 edition. Includes 144 figures and 35 tables.
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 Statistical and Inductive Probabilities
by Hugues Leblanc
This treatment addresses a decades-old dispute among probability theorists, asserting that both statistical and inductive probabilities may be treated as sentence-theoretic measurements, and that the latter qualify as estimates of the former. 1962 edition.
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| |  Statistics of Extremes
by E. J. Gumbel
This classic text covers order statistics and their exceedances; exact distribution of extremes; the 1st asymptotic distribution; uses of the 1st, 2nd, and 3rd asymptotes; more. 1958 edition. Includes 44 tables and 97 graphs.
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 Chance, Luck, and Statistics
by Horace C. Levinson
In simple, non-technical language, this volume explores the fundamentals governing chance and applies them to sports, government, and business. "Clear and lively . . . remarkably accurate." — Scientific Monthly.
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Products in Probability and Statistics | | |  | Applied Matrix Algebra in the Statistical Sciences
by Alexander Basilevsky
This comprehensive text offers teachings relevant to both applied and theoretical branches of matrix algebra and provides a bridge between linear algebra and statistical models. Appropriate for advanced undergraduate and graduate students. 1983 edition.
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| |  | Applied Probability Models with Optimization Applications
by Sheldon M. Ross
Concise advanced-level introduction to stochastic processes that arise in applied probability. Poisson process, renewal theory, Markov chains, Brownian motion, much more. Problems. References. Bibliography. 1970 edition.
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|  | 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.
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|  | Branching Processes
by K. B. Athreya, P. E. Ney
This unified treatment surveys the Galton-Watson process, potential theory, one dimensional continuous time Markov branching processes, age-dependent processes, multi-type branching processes, and special processes. Appropriate for graduate and advanced undergraduate students. 1972 edition.
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|  | Catastrophe Theory and Its Applications
by Tim Poston, Ian Stewart
First integrated treatment of main ideas behind René Thom's theory of catastrophes stresses detailed applications in the physical sciences. Mathematics of theory explained with a minimum of technicalities. Over 200 illustrations. 1978 edition.
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| | Chance, Luck, and Statistics
by Horace C. Levinson
In simple, non-technical language, this volume explores the fundamentals governing chance and applies them to sports, government, and business. "Clear and lively . . . remarkably accurate." — Scientific Monthly.
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|  | Concepts of Probability Theory: Second Revised Edition
by Paul E. Pfeiffer
Using the Kolmogorov model, this intermediate-level text discusses random variables, probability distributions, mathematical expectation, random processes, more. For advanced undergraduates students of science, engineering, or math. Includes problems with answers and six appendixes. 1965 edition.
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|  | Dynamic Probabilistic Systems, Volume I: Markov Models
by Ronald A. Howard
An integrated work in two volumes, this text teaches readers to formulate, analyze, and evaluate Markov models. The first volume treats basic process; the second, semi-Markov and decision processes. 1971 edition.
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| |  | An Elementary Introduction to the Theory of Probability
by B. V. Gnedenko, A. Ya. Khinchin
Explores concept of probability, surveys rules for addition and multiplication of probabilities, conditional probability, total probability, Bayes formula, Bernoulli's scheme, random variables, the Chebychev inequality, distribution curves, more.
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|  | 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.
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| | Experimental Statistics
by Mary Gibbons Natrella
A handbook for those seeking engineering information and quantitative data for designing, developing, constructing, and testing equipment. Covers the planning of experiments, the analyzing of extreme-value data; and more. 1966 edition. Index. Includes 52 figures and 76 tables.
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|  | Fifty Challenging Problems in Probability with Solutions
by Frederick Mosteller
Remarkable puzzlers, graded in difficulty, illustrate elementary and advanced aspects of probability. These problems were selected for originality, general interest, or because they demonstrate valuable techniques. Also includes detailed solutions.
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|  | 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.
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|  | 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.
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|  | The Foundations of Statistics
by Leonard J. Savage
Classic analysis of the foundations of statistics and development of personal probability, one of the greatest controversies in modern statistical thought. Revised edition. Calculus, probability, statistics, and Boolean algebra are recommended.
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|  | Foundations of Stochastic Analysis
by M. M. Rao
This volume considers fundamental theories and contrasts the natural interplay between real and abstract methods. No prior knowledge of probability is assumed. Numerous problems, most with hints. 1981 edition.
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| |  | 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.
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