Probability, Random Variables, and Stochastic Processes
Probability, Random Variables, and Stochastic Processes

Author: Athanasios Papoulis

Publisher: McGraw-Hill Education

Published: 2002

Total Pages: 852

ISBN-13: 9780071226615

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The fourth edition of Probability, Random Variables and Stochastic Processes has been updated significantly from the previous edition, and it now includes co-author S. Unnikrishna Pillai of Polytechnic University. The book is intended for a senior/graduate level course in probability and is aimed at students in electrical engineering, math, and physics departments. The authors' approach is to develop the subject of probability theory and stochastic processes as a deductive discipline and to illustrate the theory with basic applications of engineering interest. Approximately 1/3 of the text is new material--this material maintains the style and spirit of previous editions. In order to bridge the gap between concepts and applications, a number of additional examples have been added for further clarity, as well as several new topics.

Probability and Stochastic Processes
Probability and Stochastic Processes

Author: Roy D. Yates

Publisher: John Wiley & Sons

Published: 2014-01-28

Total Pages: 514

ISBN-13: 1118324560

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This text introduces engineering students to probability theory and stochastic processes. Along with thorough mathematical development of the subject, the book presents intuitive explanations of key points in order to give students the insights they need to apply math to practical engineering problems. The first five chapters contain the core material that is essential to any introductory course. In one-semester undergraduate courses, instructors can select material from the remaining chapters to meet their individual goals. Graduate courses can cover all chapters in one semester.

Probability & Statistics
Probability & Statistics

Author: Athanasios Papoulis

Publisher: Pearson

Published: 1990

Total Pages: 474

ISBN-13:

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A developed, complete treatment of undergraduate probability and statistics by a very well known author. The approach develops a unified theory presented with clarity and economy. Included many examples and applications. Appropriate for an introductory undergraduate course in probability and statistics for students in engineering, math, the physical sciences, and computer science.(vs. Walpole/Myers, Miller/Freund, Devore, Scheaffer/McClave, Milton/Arnold)

Introduction to Stochastic Processes
Introduction to Stochastic Processes

Author: Gregory F. Lawler

Publisher: CRC Press

Published: 2018-10-03

Total Pages: 249

ISBN-13: 1482286114

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Emphasizing fundamental mathematical ideas rather than proofs, Introduction to Stochastic Processes, Second Edition provides quick access to important foundations of probability theory applicable to problems in many fields. Assuming that you have a reasonable level of computer literacy, the ability to write simple programs, and the access to software for linear algebra computations, the author approaches the problems and theorems with a focus on stochastic processes evolving with time, rather than a particular emphasis on measure theory. For those lacking in exposure to linear differential and difference equations, the author begins with a brief introduction to these concepts. He proceeds to discuss Markov chains, optimal stopping, martingales, and Brownian motion. The book concludes with a chapter on stochastic integration. The author supplies many basic, general examples and provides exercises at the end of each chapter. New to the Second Edition: Expanded chapter on stochastic integration that introduces modern mathematical finance Introduction of Girsanov transformation and the Feynman-Kac formula Expanded discussion of Itô's formula and the Black-Scholes formula for pricing options New topics such as Doob's maximal inequality and a discussion on self similarity in the chapter on Brownian motion Applicable to the fields of mathematics, statistics, and engineering as well as computer science, economics, business, biological science, psychology, and engineering, this concise introduction is an excellent resource both for students and professionals.

Probability, Statistics, and Stochastic Processes
Probability, Statistics, and Stochastic Processes

Author: Peter Olofsson

Publisher: John Wiley & Sons

Published: 2012-05-22

Total Pages: 573

ISBN-13: 0470889748

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Praise for the First Edition ". . . an excellent textbook . . . well organized and neatly written." —Mathematical Reviews ". . . amazingly interesting . . ." —Technometrics Thoroughly updated to showcase the interrelationships between probability, statistics, and stochastic processes, Probability, Statistics, and Stochastic Processes, Second Edition prepares readers to collect, analyze, and characterize data in their chosen fields. Beginning with three chapters that develop probability theory and introduce the axioms of probability, random variables, and joint distributions, the book goes on to present limit theorems and simulation. The authors combine a rigorous, calculus-based development of theory with an intuitive approach that appeals to readers' sense of reason and logic. Including more than 400 examples that help illustrate concepts and theory, the Second Edition features new material on statistical inference and a wealth of newly added topics, including: Consistency of point estimators Large sample theory Bootstrap simulation Multiple hypothesis testing Fisher's exact test and Kolmogorov-Smirnov test Martingales, renewal processes, and Brownian motion One-way analysis of variance and the general linear model Extensively class-tested to ensure an accessible presentation, Probability, Statistics, and Stochastic Processes, Second Edition is an excellent book for courses on probability and statistics at the upper-undergraduate level. The book is also an ideal resource for scientists and engineers in the fields of statistics, mathematics, industrial management, and engineering.

Fundamentals of Applied Probability and Random Processes
Fundamentals of Applied Probability and Random Processes

Author: Oliver Ibe

Publisher: Academic Press

Published: 2014-06-13

Total Pages: 457

ISBN-13: 0128010355

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The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book's clear writing style and homework problems make it ideal for the classroom or for self-study. - Demonstrates concepts with more than 100 illustrations, including 2 dozen new drawings - Expands readers' understanding of disruptive statistics in a new chapter (chapter 8) - Provides new chapter on Introduction to Random Processes with 14 new illustrations and tables explaining key concepts. - Includes two chapters devoted to the two branches of statistics, namely descriptive statistics (chapter 8) and inferential (or inductive) statistics (chapter 9).

Probability and Statistics
Probability and Statistics

Author: Michael J. Evans

Publisher: Macmillan

Published: 2004

Total Pages: 704

ISBN-13: 9780716747420

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Unlike traditional introductory math/stat textbooks, Probability and Statistics: The Science of Uncertainty brings a modern flavor based on incorporating the computer to the course and an integrated approach to inference. From the start the book integrates simulations into its theoretical coverage, and emphasizes the use of computer-powered computation throughout.* Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. They'll get a thorough grounding in probability theory, and go beyond that to the theory of statistical inference and its applications. An integrated approach to inference is presented that includes the frequency approach as well as Bayesian methodology. Bayesian inference is developed as a logical extension of likelihood methods. A separate chapter is devoted to the important topic of model checking and this is applied in the context of the standard applied statistical techniques. Examples of data analyses using real-world data are presented throughout the text. A final chapter introduces a number of the most important stochastic process models using elementary methods. *Note: An appendix in the book contains Minitab code for more involved computations. The code can be used by students as templates for their own calculations. If a software package like Minitab is used with the course then no programming is required by the students.

Schaum's Outline of Probability, Random Variables, and Random Processes, 3/E (Enhanced Ebook)
Schaum's Outline of Probability, Random Variables, and Random Processes, 3/E (Enhanced Ebook)

Author: Hwei P. Hsu

Publisher: McGraw Hill Professional

Published: 2014-03-14

Total Pages: 1049

ISBN-13: 0071824847

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The ideal review for the thousands of electrical engineering college students who enroll in probability, variables, and processes courses Schaum's Outline of Probability, Random Variables, and Random Processes mirrors the courses in scope and sequence to help enrolled students understand basic concepts and offer extra practice on topics such as bivariate random variables, joint distribution functions, moment generating functions, Poisson processes, Wiener processes, power spectral densities, and white noise. Coverage will also include response of linear systems to random outputs, Fourier series and Karhunen-Loeve expansions, Fourier transform of random processes, parameter estimation, Bayes' estimation, and mean square estimation. Features Outline format supplies a concise guide to the standard college courses in probability, variables, and processes 405 solved problems New chapter on statistical communication theory Additional material on distributions, the Markov Process, and martingales Supports all the major textbooks for probability, variables, and processes courses

One Thousand Exercises in Probability
One Thousand Exercises in Probability

Author: Geoffrey Grimmett

Publisher: Oxford University Press

Published: 2001-05-24

Total Pages: 452

ISBN-13: 9780198572213

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This guide provides a wide-ranging selection of illuminating, informative and entertaining problems, together with their solution. Topics include modelling and many applications of probability theory.

Essentials of Stochastic Processes
Essentials of Stochastic Processes

Author: Richard Durrett

Publisher: Springer

Published: 2016-11-07

Total Pages: 282

ISBN-13: 3319456148

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Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing. One can only learn a subject by seeing it in action, so there are a large number of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding. Drawing from teaching experience and student feedback, there are many new examples and problems with solutions that use TI-83 to eliminate the tedious details of solving linear equations by hand, and the collection of exercises is much improved, with many more biological examples. Originally included in previous editions, material too advanced for this first course in stochastic processes has been eliminated while treatment of other topics useful for applications has been expanded. In addition, the ordering of topics has been improved; for example, the difficult subject of martingales is delayed until its usefulness can be applied in the treatment of mathematical finance.