*An Introduction*

Author: Geoffrey Grimmett,Dominic Welsh

Publisher: Oxford University Press

ISBN: 019870996X

Category: Mathematics

Page: 270

View: 1577

Skip to content
# Nothing Found

### Probability

Probability is an area of mathematics of tremendous contemporary importance across all aspects of human endeavour. This book is a compact account of the basic features of probability and random processes at the level of first and second year mathematics undergraduates and Masters' students in cognate fields. It is suitable for a first course in probability, plus a follow-up course in random processes including Markov chains.Three specialfeatures of this book are its modest size, the fairly broad range of topics covered, and its approach to mathematical rigour: not everything is rigorous, but the need for rigour is explained wherenecessary.This second edition develops the success of the first edition through an updated presentation, an extensive new chapter on Markov chains, and a number of new sections to ensure comprehensive coverage of the syllabi at major universities.

### Probability

Excellent basic text covers set theory, probability theory for finite sample spaces, binomial theorem, probability distributions, means, standard deviations, probability function of binomial distribution, more. Includes 360 problems with answers for half.

### Probability: An Introduction

Probability: An Introduction provides the fundamentals, requiring minimal algebraic skills from the student. It begins with an introduction to sets and set operations, progresses to counting techniques, and then presents probability in an axiomatic way, never losing sight of elucidating the subject through concrete examples. The book contains numerous examples and solved exercises taken from various fields, and includes computer explorations using Maple.

### Probability

Praise for the First Edition "This is a well-written and impressively presented introduction to probability and statistics. The text throughout is highly readable, and the author makes liberal use of graphs and diagrams to clarify the theory." - The Statistician Thoroughly updated, Probability: An Introduction with Statistical Applications, Second Edition features a comprehensive exploration of statistical data analysis as an application of probability. The new edition provides an introduction to statistics with accessible coverage of reliability, acceptance sampling, confidence intervals, hypothesis testing, and simple linear regression. Encouraging readers to develop a deeper intuitive understanding of probability, the author presents illustrative geometrical presentations and arguments without the need for rigorous mathematical proofs. The Second Edition features interesting and practical examples from a variety of engineering and scientific fields, as well as: Over 880 problems at varying degrees of difficulty allowing readers to take on more challenging problems as their skill levels increase Chapter-by-chapter projects that aid in the visualization of probability distributions New coverage of statistical quality control and quality production An appendix dedicated to the use of Mathematica® and a companion website containing the referenced data sets Featuring a practical and real-world approach, this textbook is ideal for a first course in probability for students majoring in statistics, engineering, business, psychology, operations research, and mathematics. Probability: An Introduction with Statistical Applications, Second Edition is also an excellent reference for researchers and professionals in any discipline who need to make decisions based on data as well as readers interested in learning how to accomplish effective decision making from data.

### Introduction to Probability

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.

### High-Dimensional Probability

An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

### Numerical Probability

This textbook provides a self-contained introduction to numerical methods in probability with a focus on applications to finance. Topics covered include the Monte Carlo simulation (including simulation of random variables, variance reduction, quasi-Monte Carlo simulation, and more recent developments such as the multilevel paradigm), stochastic optimization and approximation, discretization schemes of stochastic differential equations, as well as optimal quantization methods. The author further presents detailed applications to numerical aspects of pricing and hedging of financial derivatives, risk measures (such as value-at-risk and conditional value-at-risk), implicitation of parameters, and calibration. Aimed at graduate students and advanced undergraduate students, this book contains useful examples and over 150 exercises, making it suitable for self-study.

### Probability

### Understanding Statistics and Probability

A book on statistical theory and applications for undergraduate and graduate students in business, management, economics, social sciences, psychology, medicine, biostatistics and alike, as well as for practitioners. It is a hands-on guide, using computer software and real-world examples as well as Monte-Carlo simulation in order to understand statistical methods and toolboxes. Covers: - Descriptive and Exploratory Statistics and Data Analysis - Probability Theory and Random Variables (Univariate and Multivariate) - Inferential Statistics (Estimation and Hypothesis Testing) - Regression and Applied Statistics (Regression Analysis, ANOVA, Generalized Linear Models) - Copulas - Bayesian Statistics - Statistical Fallacies + Webpage, Lecture Slides and Data on www.statprob.net

### Probability , An Introduction with Statistical Applications

Facts101 is your complete guide to Probability , An Introduction with Statistical Applications. In this book, you will learn topics such as as those in your book 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.

### Choice and Chance

This definitive survey of the hottest issues in inductive logic sets the stage for further classroom discussion.

### An Introduction to Probability and Statistics

A well-balanced introduction to probability theory and mathematical statistics Featuring updated material, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics. Divided intothree parts, the Third Edition begins by presenting the fundamentals and foundationsof probability. The second part addresses statistical inference, and the remainingchapters focus on special topics. An Introduction to Probability and Statistics, Third Edition includes: A new section on regression analysis to include multiple regression, logistic regression, and Poisson regression A reorganized chapter on large sample theory to emphasize the growing role of asymptotic statistics Additional topical coverage on bootstrapping, estimation procedures, and resampling Discussions on invariance, ancillary statistics, conjugate prior distributions, and invariant confidence intervals Over 550 problems and answers to most problems, as well as 350 worked out examples and 200 remarks Numerous figures to further illustrate examples and proofs throughout An Introduction to Probability and Statistics, Third Edition is an ideal reference and resource for scientists and engineers in the fields of statistics, mathematics, physics, industrial management, and engineering. The book is also an excellent text for upper-undergraduate and graduate-level students majoring in probability and statistics.

### Introduction to Probability

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

### Probability and Mathematical Statistics

Probability and Mathematical Statistics: An Introduction provides a well-balanced first introduction to probability theory and mathematical statistics. This book is organized into two sections encompassing nine chapters. The first part deals with the concept and elementary properties of probability space, and random variables and their probability distributions. This part also considers the principles of limit theorems, the distribution of random variables, and the so-called student’s distribution. The second part explores pertinent topics in mathematical statistics, including the concept of sampling, estimation, and hypotheses testing. This book is intended primarily for undergraduate statistics students.

### Knowing the Odds

John Walsh, one of the great masters of the subject, has written a superb book on probability. It covers at a leisurely pace all the important topics that students need to know, and provides excellent examples. I regret his book was not available when I taught such a course myself, a few years ago. --Ioannis Karatzas, Columbia University In this wonderful book, John Walsh presents a panoramic view of Probability Theory, starting from basic facts on mean, median and mode, continuing with an excellent account of Markov chains and martingales, and culminating with Brownian motion. Throughout, the author's personal style is apparent; he manages to combine rigor with an emphasis on the key ideas so the reader never loses sight of the forest by being surrounded by too many trees. As noted in the preface, ``To teach a course with pleasure, one should learn at the same time.'' Indeed, almost all instructors will learn something new from the book (e.g. the potential-theoretic proof of Skorokhod embedding) and at the same time, it is attractive and approachable for students. --Yuval Peres, Microsoft With many examples in each section that enhance the presentation, this book is a welcome addition to the collection of books that serve the needs of advanced undergraduate as well as first year graduate students. The pace is leisurely which makes it more attractive as a text. --Srinivasa Varadhan, Courant Institute, New York This book covers in a leisurely manner all the standard material that one would want in a full year probability course with a slant towards applications in financial analysis at the graduate or senior undergraduate honors level. It contains a fair amount of measure theory and real analysis built in but it introduces sigma-fields, measure theory, and expectation in an especially elementary and intuitive way. A large variety of examples and exercises in each chapter enrich the presentation in the text.

### An Introduction to Probability and Stochastic Processes

Detailed coverage of probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.

### Introduction to Probability

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.

### An Elementary Introduction to the Theory of Probability

This compact volume equips the reader with all the facts and principles essential to a fundamental understanding of the theory of probability. It is an introduction, no more: throughout the book the authors discuss the theory of probability for situations having only a finite number of possibilities, and the mathematics employed is held to the elementary level. But within its purposely restricted range it is extremely thorough, well organized, and absolutely authoritative. It is the only English translation of the latest revised Russian edition; and it is the only current translation on the market that has been checked and approved by Gnedenko himself. After explaining in simple terms the meaning of the concept of probability and the means by which an event is declared to be in practice, impossible, the authors take up the processes involved in the calculation of probabilities. They survey the rules for addition and multiplication of probabilities, the concept of conditional probability, the formula for total probability, Bayes's formula, Bernoulli's scheme and theorem, the concepts of random variables, insufficiency of the mean value for the characterization of a random variable, methods of measuring the variance of a random variable, theorems on the standard deviation, the Chebyshev inequality, normal laws of distribution, distribution curves, properties of normal distribution curves, and related topics. The book is unique in that, while there are several high school and college textbooks available on this subject, there is no other popular treatment for the layman that contains quite the same material presented with the same degree of clarity and authenticity. Anyone who desires a fundamental grasp of this increasingly important subject cannot do better than to start with this book. New preface for Dover edition by B. V. Gnedenko.

### An Introduction to Measure-Theoretic Probability

An Introduction to Measure-Theoretic Probability, Second Edition, employs a classical approach to teaching the basics of measure theoretic probability. This book provides in a concise, yet detailed way, the bulk of the probabilistic tools that a student working toward an advanced degree in statistics, probability and other related areas should be equipped with. This edition requires no prior knowledge of measure theory, covers all its topics in great detail, and includes one chapter on the basics of ergodic theory and one chapter on two cases of statistical estimation. Topics range from the basic properties of a measure to modes of convergence of a sequence of random variables and their relationships; the integral of a random variable and its basic properties; standard convergence theorems; standard moment and probability inequalities; the Hahn-Jordan Decomposition Theorem; the Lebesgue Decomposition T; conditional expectation and conditional probability; theory of characteristic functions; sequences of independent random variables; and ergodic theory. There is a considerable bend toward the way probability is actually used in statistical research, finance, and other academic and nonacademic applied pursuits. Extensive exercises and practical examples are included, and all proofs are presented in full detail. Complete and detailed solutions to all exercises are available to the instructors on the book companion site. This text will be a valuable resource for graduate students primarily in statistics, mathematics, electrical and computer engineering or other information sciences, as well as for those in mathematical economics/finance in the departments of economics. Provides in a concise, yet detailed way, the bulk of probabilistic tools essential to a student working toward an advanced degree in statistics, probability, and other related fields Includes extensive exercises and practical examples to make complex ideas of advanced probability accessible to graduate students in statistics, probability, and related fields All proofs presented in full detail and complete and detailed solutions to all exercises are available to the instructors on book companion site Considerable bend toward the way probability is used in statistics in non-mathematical settings in academic, research and corporate/finance pursuits.

### Probability: A Very Short Introduction

Making good decisions under conditions of uncertainty - which is the norm - requires a sound appreciation of the way random chance works. As analysis and modelling of most aspects of the world, and all measurement, are necessarily imprecise and involve uncertainties of varying degrees, the understanding and management of probabilities is central to much work in the sciences and economics. In this Very Short Introduction, John Haigh introduces the ideas of probability and different philosophical approaches to probability, and gives a brief account of the history of development of probability theory, from Galileo and Pascal to Bayes, Laplace, Poisson, and Markov. He describes the basic probability distributions, and goes on to discuss a wide range of applications in science, economics, and a variety of other contexts such as games and betting. He concludes with an intriguing discussion of coincidences and some curious paradoxes. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

Full PDF eBook Download Free

*An Introduction*

Author: Geoffrey Grimmett,Dominic Welsh

Publisher: Oxford University Press

ISBN: 019870996X

Category: Mathematics

Page: 270

View: 1577

*An Introduction*

Author: Samuel Goldberg

Publisher: Courier Corporation

ISBN: 0486318540

Category: Mathematics

Page: 352

View: 7646

*An Introduction*

Author: David A. Santos

Publisher: Jones & Bartlett Publishers

ISBN: 1449666132

Category: Mathematics

Page: 406

View: 8546

*An Introduction with Statistical Applications*

Author: John J. Kinney

Publisher: John Wiley & Sons

ISBN: 111894710X

Category: Mathematics

Page: 480

View: 4256

Author: John E. Freund

Publisher: Courier Corporation

ISBN: 0486158438

Category: Mathematics

Page: 247

View: 2465

*An Introduction with Applications in Data Science*

Author: Roman Vershynin

Publisher: Cambridge University Press

ISBN: 1108415199

Category: Business & Economics

Page: 296

View: 351

*An Introduction with Applications to Finance*

Author: Gilles Pagès

Publisher: Springer

ISBN: 3319902768

Category: Mathematics

Page: 579

View: 8725

*an introduction with applications*

Author: Albert J. Simone

Publisher: N.A

ISBN: N.A

Category: Probabilities

Page: 163

View: 5783

*An Introduction to Methods, Techniques and Computer Applications*

Author: Daniel Roesch

Publisher: Createspace Independent Publishing Platform

ISBN: 9781540622594

Category:

Page: 660

View: 4273

Author: CTI Reviews

Publisher: Cram101 Textbook Reviews

ISBN: 1497045215

Category: Education

Page: 40

View: 541

*An Introduction to Inductive Logic*

Author: Brian Skyrms

Publisher: Wadsworth Publishing Company

ISBN: 9780534557379

Category: Education

Page: 174

View: 2883

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

Publisher: John Wiley & Sons

ISBN: 1118799658

Category: Mathematics

Page: 728

View: 3628

Author: Charles Miller Grinstead,James Laurie Snell

Publisher: American Mathematical Soc.

ISBN: 0821894145

Category: Probabilities

Page: 510

View: 382

*An Introduction*

Author: Eugene Lukacs

Publisher: Academic Press

ISBN: 1483269205

Category: Mathematics

Page: 254

View: 1706

*An Introduction to Probability*

Author: John B. Walsh

Publisher: American Mathematical Soc.

ISBN: 0821885324

Category: Mathematics

Page: 421

View: 3556

Author: James L. Melsa,Andrew P. Sage

Publisher: Courier Corporation

ISBN: 0486490998

Category: Mathematics

Page: 403

View: 9152

Author: Joseph K. Blitzstein,Jessica Hwang

Publisher: CRC Press

ISBN: 1498759769

Category: Mathematics

Page: 596

View: 2215

Author: Boris Vladimirovich Gnedenko,Aleksandr I?Akovlevich Khinchin

Publisher: Courier Corporation

ISBN: 9780486601557

Category: Mathematics

Page: 130

View: 5933

Author: George G. Roussas

Publisher: Academic Press

ISBN: 0128002905

Category: Mathematics

Page: 426

View: 2136

Author: John Haigh

Publisher: OUP Oxford

ISBN: 0191636835

Category: Mathematics

Page: 144

View: 9788