## A Course in Probability

**Author**: Neil A. Weiss,Paul T. Holmes,Michael Hardy

**Publisher:**Pearson College Division

**ISBN:**9780201774719

**Category:**Mathematics

**Page:**789

**View:**5045

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This text is intended primarily for readers interested in mathematical probability as applied to mathematics, statistics, operations research, engineering, and computer science. It is also appropriate for mathematically oriented readers in the physical and social sciences. Prerequisite material consists of basic set theory and a firm foundation in elementary calculus, including infinite series, partial differentiation, and multiple integration. Some exposure to rudimentary linear algebra (e.g., matrices and determinants) is also desirable. This text includes pedagogical techniques not often found in books at this level, in order to make the learning process smooth, efficient, and enjoyable. Fundamentals of Probability: Probability Basics. Mathematical Probability. Combinatorial Probability. Conditional Probability and Independence.Discrete Random Variables: Discrete Random Variables and Their Distributions. Jointly Discrete Random Variables. Expected Value of Discrete Random Variables.Continuous Random Variables: Continuous Random Variables and Their Distributions. Jointly Continuous Random Variables. Expected Value of Continuous Random Variables.Limit Theorems and Advanced Topics: Generating Functions and Limit Theorems. Additional Topics. For all readers interested in probability.

## Weighing the Odds

*A Course in Probability and Statistics*

**Author**: David Williams

**Publisher:**Cambridge University Press

**ISBN:**9780521006187

**Category:**Mathematics

**Page:**547

**View:**9744

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Advanced textbook; many examples and exercises, often with hints or solutions; code provided for computational examples and simulations.

## A Course in Probability Theory

**Author**: Kai Lai Chung

**Publisher:**Academic Press

**ISBN:**0121741516

**Category:**Mathematics

**Page:**419

**View:**2789

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Since the publication of the first edition of this classic textbook over thirty years ago, tens of thousands of students have used A Course in Probability Theory. New in this edition is an introduction to measure theory that expands the market, as this treatment is more consistent with current courses. While there are several books on probability, Chung's book is considered a classic, original work in probability theory due to its elite level of sophistication.

## A Course in Probability and Statistics

**Author**: Charles Joel Stone

**Publisher:**Cengage Learning

**ISBN:**N.A

**Category:**Mathematics

**Page:**838

**View:**5340

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This author's modern approach is intended primarily for honors undergraduates or undergraduates with a good math background taking a mathematical statistics or statistical inference course. The author takes a finite-dimensional functional modeling viewpoint (in contrast to the conventional parametric approach) to strengthen the connection between statistical theory and statistical methodology.

## e-Study Guide for: A Course in Probability Theory, Revised Edition by Kai Lai Chung, ISBN 9780121741518

**Author**: Cram101 Textbook Reviews

**Publisher:**Cram101 Textbook Reviews

**ISBN:**1467213209

**Category:**Education

**Page:**24

**View:**7226

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Never Highlight a Book Again! Just the FACTS101 study guides give the student the textbook outlines, highlights, practice quizzes and optional access to the full practice tests for their textbook.

## Outlines and Highlights for a Course in Probability by Weiss, Isbn

*9780201774719*

**Author**: Cram101 Textbook Reviews

**Publisher:**Academic Internet Pub Incorporated

**ISBN:**9781617442148

**Category:**Education

**Page:**228

**View:**4626

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Never HIGHLIGHT a Book Again! Virtually all of the testable terms, concepts, persons, places, and events from the textbook are included. Cram101 Just the FACTS101 studyguides give all of the outlines, highlights, notes, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanys: 9780201774719 .

## A Course in Mathematical Statistics

**Author**: George G. Roussas

**Publisher:**Elsevier

**ISBN:**0080493149

**Category:**Mathematics

**Page:**572

**View:**6309

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A Course in Mathematical Statistics, Second Edition, contains enough material for a year-long course in probability and statistics for advanced undergraduate or first-year graduate students, or it can be used independently for a one-semester (or even one-quarter) course in probability alone. It bridges the gap between high and intermediate level texts so students without a sophisticated mathematical background can assimilate a fairly broad spectrum of the theorems and results from mathematical statistics. The coverage is extensive, and consists of probability and distribution theory, and statistical inference. * Contains 25% new material * Includes the most complete coverage of sufficiency * Transformation of Random Vectors * Sufficiency / Completeness / Exponential Families * Order Statistics * Elements of Nonparametric Density Estimation * Analysis of Variance (ANOVA) * Regression Analysis * Linear Models

## A First Course in Probability

**Author**: Tapas K. Chandra,Dipak Chatterjee

**Publisher:**CRC Press

**ISBN:**9780849309434

**Category:**Mathematics

**Page:**467

**View:**4084

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The advancement of science in the twentieth century is marked by a special feature -- its transition from deterministic phenomena to probabilistic phenomena. For this reason the probability theory is introduced at the earliest possible level of any academic pursuit. Written at an introductory level, A First Course in Probability takes an intuitive approach to proving the ethereal existence of probability, developing the subject step-by-step to show the accessibility of probability theory. The authors provide hundreds of problems from almost all spheres of life to demonstrate how probability plays a decisive role. Numerous routine and simple examples are solved throughout the text to demonstrate various techniques of solving practical problems. The more difficult problems are solved at the end of each chapter under the heading, "Miscellaneous Examples," and these are useful in solving problems in different competitive examinations. Easy to understand and up-to-date, the text incorporates all the fundamental results while bringing forth the latest results. Some topics that can be avoided in the first reading are star-marked in the text.

## A Basic Course in Probability Theory

**Author**: Rabi Bhattacharya,Edward C. Waymire

**Publisher:**Springer Science & Business Media

**ISBN:**0387719393

**Category:**Mathematics

**Page:**220

**View:**4135

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Introductory Probability is a pleasure to read and provides a fine answer to the question: How do you construct Brownian motion from scratch, given that you are a competent analyst? There are at least two ways to develop probability theory. The more familiar path is to treat it as its own discipline, and work from intuitive examples such as coin flips and conundrums such as the Monty Hall problem. An alternative is to first develop measure theory and analysis, and then add interpretation. Bhattacharya and Waymire take the second path.

## A Graduate Course in Probability

**Author**: Howard G. Tucker

**Publisher:**Courier Corporation

**ISBN:**0486493032

**Category:**Mathematics

**Page:**288

**View:**9703

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"Suitable for a graduate course in analytic probability, this text requires only a limited background in real analysis. Topics include probability spaces and distributions, stochastic independence, basic limiting options, strong limit theorems for independent random variables, central limit theorem, conditional expectation and Martingale theory, and an introduction to stochastic processes"--

## A Course in Real Analysis

**Author**: John N. McDonald,Neil A. Weiss

**Publisher:**Taylor & Francis US

**ISBN:**9780127428307

**Category:**Mathematics

**Page:**745

**View:**9572

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A Course in Real Analysis provides a firm foundation in real analysis concepts and principles while presenting a broad range of topics in a clear and concise manner. This student-oriented text balances theory and applications, and contains a wealth of examples and exercises. Throughout the text, the authors adhere to the idea that most students learn more efficiently by progressing from the concrete to the abstract. McDonald and Weiss have also created real application chapters on probability theory, harmonic analysis, and dynamical systems theory. The text offers considerable flexibility in the choice of material to cover. * Motivation of Key Concepts: The importance of and rationale behind key ideas are made transparent * Illustrative Examples: Roughly 200 examples are presented to illustrate definitions and results * Abundant and Varied Exercises: Over 1200 exercises are provided to promote understanding * Biographies: Each chapter begins with a brief biography of a famous mathematician

## Elementare Wahrscheinlichkeitstheorie und stochastische Prozesse

**Author**: Kai L. Chung

**Publisher:**Springer-Verlag

**ISBN:**3642670334

**Category:**Mathematics

**Page:**346

**View:**3326

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Aus den Besprechungen: "Unter den zahlreichen Einführungen in die Wahrscheinlichkeitsrechnung bildet dieses Buch eine erfreuliche Ausnahme. Der Stil einer lebendigen Vorlesung ist über Niederschrift und Übersetzung hinweg erhalten geblieben. In jedes Kapitel wird sehr anschaulich eingeführt. Sinn und Nützlichkeit der mathematischen Formulierungen werden den Lesern nahegebracht. Die wichtigsten Zusammenhänge sind als mathematische Sätze klar formuliert." #FREQUENZ#1

## A Course in Probability

**Author**: CTI Reviews

**Publisher:**Cram101 Textbook Reviews

**ISBN:**1490267514

**Category:**Education

**Page:**21

**View:**2496

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Facts101 is your complete guide to A Course in Probability. In this book, you will learn topics such as COMBINATORIAL PROBABILITY, CONDITIONAL PROBABILITY AND INDEPENDENCE, DISCRETE RANDOM VARIABLES AND THEIR DISTRIBUTIONS, and JOINTLY DISCRETE RANDOM VARIABLES plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.

## A First Course in Probability Models and Statistical Inference

**Author**: James H.C. Creighton

**Publisher:**Springer Science & Business Media

**ISBN:**1441985409

**Category:**Mathematics

**Page:**719

**View:**1637

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Welcome to new territory: A course in probability models and statistical inference. The concept of probability is not new to you of course. You've encountered it since childhood in games of chance-card games, for example, or games with dice or coins. And you know about the "90% chance of rain" from weather reports. But once you get beyond simple expressions of probability into more subtle analysis, it's new territory. And very foreign territory it is. You must have encountered reports of statistical results in voter sur veys, opinion polls, and other such studies, but how are conclusions from those studies obtained? How can you interview just a few voters the day before an election and still determine fairly closely how HUN DREDS of THOUSANDS of voters will vote? That's statistics. You'll find it very interesting during this first course to see how a properly designed statistical study can achieve so much knowledge from such drastically incomplete information. It really is possible-statistics works! But HOW does it work? By the end of this course you'll have understood that and much more. Welcome to the enchanted forest.

## Introduction to Probability and Statistics for Engineers and Scientists

**Author**: Sheldon M. Ross

**Publisher:**Academic Press

**ISBN:**0123948428

**Category:**Mathematics

**Page:**686

**View:**9303

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Introduction to Probability and Statistics for Engineers and Scientists 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 tremendously clear exposition, plus real-data examples and exercises throughout the text. Numerous exercises, examples, and applications connect probability theory to everyday statistical problems and situations. Clear exposition by a renowned expert author Real data examples that use significant real data from actual studies across life science, engineering, computing and business End of Chapter review material that emphasizes key ideas as well as the risks associated with practical application of the material 25% New Updated problem sets and applications, that demonstrate updated applications to engineering as well as biological, physical and computer science New additions to proofs in the estimation section New coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions.

## A First Course in Probability

**Author**: Sheldon M. Ross

**Publisher:**Pearson College Division

**ISBN:**9780321794772

**Category:**Mathematics

**Page:**467

**View:**9089

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A First Course in Probability, Ninth 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 calculus.

## An Intermediate Course in Probability

**Author**: Allan Gut

**Publisher:**Springer Science & Business Media

**ISBN:**1441901620

**Category:**Mathematics

**Page:**303

**View:**2436

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This is the only book that gives a rigorous and comprehensive treatment with lots of examples, exercises, remarks on this particular level between the standard first undergraduate course and the first graduate course based on measure theory. There is no competitor to this book. The book can be used in classrooms as well as for self-study.

## Probability Theory

*A First Course in Probability Theory and Statistics*

**Author**: Werner Linde

**Publisher:**Walter de Gruyter GmbH & Co KG

**ISBN:**3110466198

**Category:**Mathematics

**Page:**409

**View:**9218

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This book is intended as an introduction to Probability Theory and Mathematical Statistics for students in mathematics, the physical sciences, engineering, and related fields. It is based on the author’s 25 years of experience teaching probability and is squarely aimed at helping students overcome common difficulties in learning the subject. The focus of the book is an explanation of the theory, mainly by the use of many examples. Whenever possible, proofs of stated results are provided. All sections conclude with a short list of problems. The book also includes several optional sections on more advanced topics. This textbook would be ideal for use in a first course in Probability Theory. Contents: Probabilities Conditional Probabilities and Independence Random Variables and Their Distribution Operations on Random Variables Expected Value, Variance, and Covariance Normally Distributed Random Vectors Limit Theorems Mathematical Statistics Appendix Bibliography Index

## A First Course in Probability and Statistics

**Author**: B. L. S. Prakasa Rao

**Publisher:**World Scientific

**ISBN:**9812836535

**Category:**Mathematics

**Page:**317

**View:**8684

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This book provides a clear exposition of the theory of probability along with applications in statistics.

## A Course in Simulation

**Author**: Sheldon M. Ross

**Publisher:**MacMillan Publishing Company

**ISBN:**9780024038913

**Category:**Mathematics

**Page:**202

**View:**1603

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Mathematics of Computing -- Probability and Statistics.