Ross S.M. Introduction to Probability Models

MIT, 2000. - 284 pages. An intuitive, yet precise introduction to probability theory, stochastic processes, and probabilistic models used in science, engineering, economics, and related fields. This is the currently used textbook for "Probabilistic Systems Analysis, " an introductory probability course at the Massachusetts Institute of Technology, attended by a large number of undergraduate and graduate students. The book covers the fundamentals...

2nd Edition. Wiley series in probability and statistics. Wiley & Sons, Ltd, 2006. - 598 pages. Contents: Introduction: The Bayesian Method, its Benefits and Implementation Bayesian Model Choice, Comparison and Checking The Major Densities and their Application Normal Linear Regression, General Linear Models and Log-Linear Models Hierarchical Priors for Pooling Strength and Overdispersed Regression Modelling Discrete Mixture Priors Multinomia...

John Wiley & Sons, 1963. - 695 pages. Probability theory can be understood as a mathematical model for the intuitive notion of uncertainty. Without probability theory all the stochastic models in Physics, Biology, and Economics would either not have been developed or would not be rigorous. Also, probability is used in many branches of pure mathematics, even in branches one does not expect this, like in convex geometry.

(Математическая статистика - Chapman & Hall/CRC, 2000). This book is intended as a textbook (or reference) for a full year Master’s level (or senior level undergraduate) course in mathematical statistics aimed at students in statistics, biostatistics, and related fields. Contents: Introduction to Probability. Random experiments. Probability measures. Conditional probability and independence. Random variables. Transformations of random variab...

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...

Prentice Hall, 2009. - 552 pages. 8th Edition A First Course in Probability, Eighth Edition, features clear and intuitive explanations of the mathematics of probability theory, outstanding problem sets, and a variety of diverse examples and applications. This book is ideal for an upper-level undergraduate or graduate level introduction to probability for math, science, engineering and business students. It assumes a background in elementary cal...

7th Edition. Publisher: Prentice Hall, 2005. - 147 pages. This introduction presents the mathematical theory of probability for readers in the fields of engineering and the sciences who possess knowledge of elementary calculus. Presents new examples and exercises throughout. Offers a new section that presents an elegant way of computing the moments of random variables defined as the number of events that occur. Gives applications to binomial, hy...

Probabilitybookstore.com, 2007. - 212 pages. The 2006 INFORMS Expository Writing Award-winning and best-selling author Sheldon Ross (University of Southern California) teams up with Erol Pek?z (Boston University) to bring you this textbook for undergraduate and graduate students in statistics, mathematics, engineering, finance, and actuarial science. This is a guided tour designed to give familiarity with advanced topics in probability without h...

Book 2007, 782p, ISBN-13: 978-0-12-598062-3 Ninth Edition content Introduction to Probability Theory Introduction to Probability Theory Conditional Probability and Conditional Expectation Markov Chains The Exponential Distribution and the Poisson Process Continuous-Time Markov Chains Renewal Theory and Its Applications Queueing Theory Reliability Theory Brownian Motion and Stationary Processes Simulation Appendix: Solutions to Starred Exercises

189 pages. This introduction presents the mathematical theory of probability for readers in the fields of engineering and the sciences who possess knowledge of elementary calculus. Presents new examples and exercises throughout. Offers a new section that presents an elegant way of computing the moments of random variables defined as the number of events that occur. Gives applications to binomial, hypergeometric, and negative hypergeometric random...