McLaughlin M.P. A Compendium of Common Probability Distributions

Springer, 2010. - 494 Pages. This is a text encompassing all of the standard topics in introductory probability theory, together with a significant amount of optional material of emerging importance. The emphasis is on a lucid and accessible writing style, mixed with a large number of interesting examples of a diverse nature. The text will prepare students extremely well for courses in more advanced probability and in statistical theory and for...

Addison-wesley publishing company September 1989 730 pages Probability & Statistics was written for a one or two semester probability and statistics course offered primarily at four-year institutions and taken mostly by sophomore and junior level students, majoring in mathematics or statistics. Calculus is a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus. The revision of this wel...

Prentice Hill, 1999. - 511 pages. This book is a valuable reference to Basic Probability and related problems, featuring unique discussions published in recent journals to support individual investigation. Chapter topics include combinatorial methods, conditional probability and independence, random variables, distributions, and simulation. For professionals in the fields of computer and actuarial science, electrical and industrial engineering,...

Prentice Hall, 2004. - 644 pages. Presenting probability in a natural way, this book uses interesting, carefully selected instructive examples that explain the theory, definitions, theorems, and methodology. Fundamentals of Probability has been adopted by the American Actuarial Society as one of its main references for the mathematical foundations of actuarial science. Topics include: axioms of probability; combinatorial methods; conditional...

This classic book is intended to be the first introduction to probability and statistics written with an emphasis on the analytic approach to the problems discussed. Topics include the axiomatic setup of probability theory, polynomial distribution, finite Markov chains, distribution functions and convolution, the laws of large numbers (weak and strong), characteristic functions, the central limit theorem, infinitely divisible distributions, and M...

1997. 565 pp. Electronic publication. Полностью распознано. Contents: Discrete Probability Distributions. Simulation of Discrete Probabilities. Discrete Probability Distributions. Continuous Probability Densities. Simulation of Continuous Probabilities. Continuous Density Functions. Combinatorics. Permutations. Combinations. Card Shuffling. Conditional Probability. Discrete Conditional Probability. Continuous Conditional Probability. Paradoxes. D...

1999. 510 pp. Electronic publication. Contents: Discrete Probability Distributions. Simulation of Discrete Probabilities. Discrete Probability Distributions. Continuous Probability Densities. Simulation of Continuous Probabilities. Continuous Density Functions. Combinatorics. Permutations. Combinations. Card Shuffling. Conditional Probability. Discrete Conditional Probability. Continuous Conditional Probability. Paradoxes. Distributions and Densi...

G. Jay Kerns, 2010. - 386 pages. This book was expanded from lecture materials I use in a one semester upper-division undergraduate course entitled Probability and Statistics at Youngstown State University. Those lecture materials, in turn, were based on notes that I transcribed as a graduate student at Bowling Green State University. The course for which the materials were written is 50-50 Probability and Statistics, and the attendees include m...

McGraw-Hill, 1998, 376 pages. The purpose of this book is to present a modern introduction to probability and statistics using background of calculus. For convenience the book is divided into two parts. The first deals with probability (and by itself can be used to provide an introduction to the subject), while the second deals with statistics. The book is designed to be used either as a textbook for formal course in probability and statistics or...

Morgan Kaufmann Publishers, 2009. - 400 pages. The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book...