## Introduction to Probability

**Author**: Charles Miller Grinstead,James Laurie Snell

**Publisher:**American Mathematical Soc.

**ISBN:**0821894145

**Category:**Probabilities

**Page:**510

**View:**2151

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This text is designed for an introductory probability course at the university level for sophomores, juniors, and seniors in mathematics, physical and social sciences, engineering, and computer science. It presents a thorough treatment of ideas and techniques necessary for a firm understanding of the subject. The text is also recommended for use in discrete probability courses. The material is organized so that the discrete and continuous probability discussions are presented in a separate, but parallel, manner. This organization does not emphasize an overly rigorous or formal view of probability and therefore offers some strong pedagogical value. Hence, the discrete discussions can sometimes serve to motivate the more abstract continuous probability discussions. Features: Key ideas are developed in a somewhat leisurely style, providing a variety of interesting applications to probability and showing some nonintuitive ideas. Over 600 exercises provide the opportunity for practicing skills and developing a sound understanding of ideas. Numerous historical comments deal with the development of discrete probability. The text includes many computer programs that illustrate the algorithms or the methods of computation for important problems. The book is a beautiful introduction to probability theory at the beginning level. The book contains a lot of examples and an easy development of theory without any sacrifice of rigor, keeping the abstraction to a minimal level. It is indeed a valuable addition to the study of probability theory. --Zentralblatt MATH

## An Introduction to Probability Theory

**Author**: K. Itô

**Publisher:**Cambridge University Press

**ISBN:**9780521269605

**Category:**Mathematics

**Page:**213

**View:**5555

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One of the most distinguished probability theorists in the world rigorously explains the basic probabilistic concepts while fostering an intuitive understanding of random phenomena.

## Introduction to Probability

**Author**: David F. Anderson,Timo Seppäläinen,Benedek Valkó

**Publisher:**Cambridge University Press

**ISBN:**110824498X

**Category:**Mathematics

**Page:**N.A

**View:**9973

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This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.

## Introduction to Probability Models

**Author**: Sheldon M. Ross

**Publisher:**Academic Press

**ISBN:**0125980620

**Category:**Mathematics

**Page:**782

**View:**2597

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Rosss classic bestseller has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. With the addition of several new sections relating to actuaries, this text is highly recommended by the Society of Actuaries.

## Introduction to Probability

**Author**: Dimitri P. Bertsekas,John N. Tsitsiklis

**Publisher:**N.A

**ISBN:**9781886529236

**Category:**Mathematics

**Page:**528

**View:**8710

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## An Introduction to Probability and Statistics

**Author**: Vijay K. Rohatgi,A. K. Md. Ehsanes Saleh

**Publisher:**John Wiley & Sons

**ISBN:**1118165683

**Category:**Mathematics

**Page:**744

**View:**8967

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The second edition of a well-received book that was published 24 years ago and continues to sell to this day, An Introduction to Probability and Statistics is now revised to incorporate new information as well as substantial updates of existing material.

## Introduction to Probability

**Author**: George G. Roussas

**Publisher:**Elsevier

**ISBN:**9780080509334

**Category:**Mathematics

**Page:**400

**View:**1097

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Roussas's Introduction to Probability features exceptionally clear explanations of the mathematics of probability theory and explores its diverse applications through numerous interesting and motivational examples. It provides a thorough introduction to the subject for professionals and advanced students taking their first course in probability. The content is based on the introductory chapters of Roussas's book, An Intoduction to Probability and Statistical Inference, with additional chapters and revisions. • Written by a well-respected author known for great exposition and readability • Boasts many real world examples • Pedagogy includes chapter summaries, tables of distributions and formulas, and answers to even-numbered exercises

## Introduction to Probability and Statistics for Engineers and Scientists

**Author**: Sheldon M. Ross

**Publisher:**Academic Press

**ISBN:**9780080919379

**Category:**Mathematics

**Page:**680

**View:**9857

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This updated text provides a superior introduction to applied probability and statistics for engineering or science majors. Ross emphasizes the manner in which probability yields insight into statistical problems; ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. Real data sets are incorporated in a wide variety of exercises and examples throughout the book, and this emphasis on data motivates the probability coverage. As with the previous editions, Ross' text has remendously clear exposition, plus real-data examples and exercises throughout the text. Numerous exercises, examples, and applications apply probability theory to everyday statistical problems and situations. New to the 4th Edition: - New Chapter on Simulation, Bootstrap Statistical Methods, and Permutation Tests - 20% New Updated problem sets and applications, that demonstrate updated applications to engineering as well as biological, physical and computer science - New Real data examples that use significant real data from actual studies across life science, engineering, computing and business - New End of Chapter review material that emphasizes key ideas as well as the risks associated with practical application of the material

## An introduction to probability theory and mathematical statistics

**Author**: V. K. Rohatgi

**Publisher:**John Wiley & Sons Inc

**ISBN:**N.A

**Category:**Mathematics

**Page:**684

**View:**7892

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Probability; Random variables and their probability distributions; Moments and generating functions; Random vectors; Some special distributions; Limit theorems; Sample moments and their distributions; The theory of point estimation; Neyman-Pearson theory of testing of hypotheses; Some further results on hypotheses testing; Confidence estimation; The general linear hypothesis; Nonparametric statistical inference; Sequential statistical inference.

## Introduction to Probability

**Author**: Joseph K. Blitzstein,Jessica Hwang

**Publisher:**CRC Press

**ISBN:**146657559X

**Category:**Mathematics

**Page:**596

**View:**5344

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Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.

## Introduction to Probability with R

**Author**: Kenneth Baclawski

**Publisher:**CRC Press

**ISBN:**9781420065220

**Category:**Mathematics

**Page:**384

**View:**8598

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Based on a popular course taught by the late Gian-Carlo Rota of MIT, with many new topics covered as well, Introduction to Probability with R presents R programs and animations to provide an intuitive yet rigorous understanding of how to model natural phenomena from a probabilistic point of view. Although the R programs are small in length, they are just as sophisticated and powerful as longer programs in other languages. This brevity makes it easy for students to become proficient in R. This calculus-based introduction organizes the material around key themes. One of the most important themes centers on viewing probability as a way to look at the world, helping students think and reason probabilistically. The text also shows how to combine and link stochastic processes to form more complex processes that are better models of natural phenomena. In addition, it presents a unified treatment of transforms, such as Laplace, Fourier, and z; the foundations of fundamental stochastic processes using entropy and information; and an introduction to Markov chains from various viewpoints. Each chapter includes a short biographical note about a contributor to probability theory, exercises, and selected answers. The book has an accompanying website with more information.

## Introduction to Probability Models, ISE

**Author**: Sheldon M. Ross

**Publisher:**Academic Press

**ISBN:**0080920179

**Category:**Mathematics

**Page:**800

**View:**3934

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Ross's classic bestseller, Introduction to Probability Models, has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It provides an introduction to elementary probability theory and stochastic processes, and shows how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. With the addition of several new sections relating to actuaries, this text is highly recommended by the Society of Actuaries. A new section (3.7) on COMPOUND RANDOM VARIABLES, that can be used to establish a recursive formula for computing probability mass functions for a variety of common compounding distributions. A new section (4.11) on HIDDDEN MARKOV CHAINS, including the forward and backward approaches for computing the joint probability mass function of the signals, as well as the Viterbi algorithm for determining the most likely sequence of states. Simplified Approach for Analyzing Nonhomogeneous Poisson processes Additional results on queues relating to the (a) conditional distribution of the number found by an M/M/1 arrival who spends a time t in the system; (b) inspection paradox for M/M/1 queues (c) M/G/1 queue with server breakdown Many new examples and exercises.

## Introduction to Probability and Statistics for Engineers

**Author**: Milan Holický

**Publisher:**Springer Science & Business Media

**ISBN:**3642383009

**Category:**Mathematics

**Page:**181

**View:**567

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The theory of probability and mathematical statistics is becoming an indispensable discipline in many branches of science and engineering. This is caused by increasing significance of various uncertainties affecting performance of complex technological systems. Fundamental concepts and procedures used in analysis of these systems are often based on the theory of probability and mathematical statistics. The book sets out fundamental principles of the probability theory, supplemented by theoretical models of random variables, evaluation of experimental data, sampling theory, distribution updating and tests of statistical hypotheses. Basic concepts of Bayesian approach to probability and two-dimensional random variables, are also covered. Examples of reliability analysis and risk assessment of technological systems are used throughout the book to illustrate basic theoretical concepts and their applications. The primary audience for the book includes undergraduate and graduate students of science and engineering, scientific workers and engineers and specialists in the field of reliability analysis and risk assessment. Except basic knowledge of undergraduate mathematics no special prerequisite is required.

## Introduction to Probability

**Author**: John E. Freund

**Publisher:**Courier Corporation

**ISBN:**0486158438

**Category:**Mathematics

**Page:**247

**View:**8258

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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.

## Introduction to probability

**Author**: James Laurie Snell

**Publisher:**N.A

**ISBN:**N.A

**Category:**Mathematics

**Page:**478

**View:**7834

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## Introduction to Probability and Statistics Using R

**Author**: G. Jay Kerns

**Publisher:**Lulu.com

**ISBN:**0557249791

**Category:**

**Page:**N.A

**View:**1619

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## Elements of Probability and Statistics

*An Introduction to Probability with de Finetti’s Approach and to Bayesian Statistics*

**Author**: Francesca Biagini,Massimo Campanino

**Publisher:**Springer

**ISBN:**3319072544

**Category:**Mathematics

**Page:**246

**View:**7970

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This book provides an introduction to elementary probability and to Bayesian statistics using de Finetti's subjectivist approach. One of the features of this approach is that it does not require the introduction of sample space – a non-intrinsic concept that makes the treatment of elementary probability unnecessarily complicate – but introduces as fundamental the concept of random numbers directly related to their interpretation in applications. Events become a particular case of random numbers and probability a particular case of expectation when it is applied to events. The subjective evaluation of expectation and of conditional expectation is based on an economic choice of an acceptable bet or penalty. The properties of expectation and conditional expectation are derived by applying a coherence criterion that the evaluation has to follow. The book is suitable for all introductory courses in probability and statistics for students in Mathematics, Informatics, Engineering, and Physics.

## A Natural Introduction to Probability Theory

**Author**: R. Meester

**Publisher:**Springer Science & Business Media

**ISBN:**9783764387242

**Category:**Mathematics

**Page:**198

**View:**4778

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Compactly written, but nevertheless very readable, appealing to intuition, this introduction to probability theory is an excellent textbook for a one-semester course for undergraduates in any direction that uses probabilistic ideas. Technical machinery is only introduced when necessary. The route is rigorous but does not use measure theory. The text is illustrated with many original and surprising examples and problems taken from classical applications like gambling, geometry or graph theory, as well as from applications in biology, medicine, social sciences, sports, and coding theory. Only first-year calculus is required.

## Introduction to Probability, Statistics, and Random Processes

*Statistics and Random Processes*

**Author**: Hossein Pishro-Nik

**Publisher:**N.A

**ISBN:**9780990637202

**Category:**Probabilities

**Page:**746

**View:**442

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The book covers basic concepts such as random experiments, probability axioms, conditional probability, and counting methods, single and multiple random variables (discrete, continuous, and mixed), as well as moment-generating functions, characteristic functions, random vectors, and inequalities; limit theorems and convergence; introduction to Bayesian and classical statistics; random processes including processing of random signals, Poisson processes, discrete-time and continuous-time Markov chains, and Brownian motion; simulation using MATLAB and R.

## An introduction to probability, decision, and inference

**Author**: Irving H. LaValle

**Publisher:**N.A

**ISBN:**N.A

**Category:**Mathematics

**Page:**767

**View:**8768

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