Key words and phrases

Brownian motion, Markov property, metric space, probability space, measurable space, stochastic process, characteristic function, Laplace transform, Borel-Cantelli lemma, continuous functions, probability measure, measurable function, martingale, signed measure, dominated convergence theorem, conditional expectation, random walk, law of large, weak topology, Lebesgue measure

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A Basic Course in Probability Theory

By Rabindra Nath Bhattacharya, Edward C. Waymire, SpringerLink (Online service), SpringerLink (Online service

Published by Springer, 2007

ISBN 0387719393, 9780387719399

210 pages

"This classic text and reference introduces probability theory for both advanced undergraduate students of statistics and scientists in related fields, drawing on real applications in the physical and biological sciences. "The book makes probability exciting." --Journal of the American Statistical Association

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An Introduction to Probability Theory

By Patrick Alfred Pierce Moran

Edition: 2, reprint, revised

Published by Oxford University Press, 1984

ISBN 0198532423, 9780198532422

542 pages

Written by two experts in the field, this book is ideal for advanced undergraduate students, graduate students, and researchers in computer science, mathematics, cognitive sciences, philosophy, artificial intelligence, statistics, and physics. It is self-contained in that it contains the basic requirements from mathematics and computer science. Included are also numerous problem sets, comments, source references, and hints to solutions of problems, as well as a great deal of new material not included in the first edition.

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An Introduction to Kolmogorov Complexity and Its Applications

By Ming Li, P. M. B. Vitányi

Contributor P. M. B. Vitányi

Edition: 2, illustrated, revised

Published by Springer, 1997

ISBN 0387948686, 9780387948683

637 pages

The use of Bayesian statistics has grown significantly in recent years, and will undoubtedly continue to do so. Applied Bayesian Modelling is the follow-up to the author's best selling book, Bayesian Statistical Modelling, and focuses on the potential applications of Bayesian techniques in a wide range of important topics in the social and health sciences. The applications are illustrated through many real-life examples and software implementation in WINBUGS - a popular software package that offers a simplified and flexible approach to statistical modelling. The book gives detailed explanations for each example - explaining fully the choice of model for each particular problem. The book ? Provides a broad and comprehensive account of applied Bayesian modelling. ? Describes a variety of model assessment methods and the flexibility of Bayesian prior specifications. ? Covers many application areas, including panel data models, structural equation and other multivariate structure models, spatial analysis, survival analysis and epidemiology. ? Provides detailed worked examples in WINBUGS to illustrate the practical application of the techniques described. All WINBUGS programs are available from an ftp site. The book provides a good introduction to Bayesian modelling and data analysis for a wide range of people involved in applied statistical analysis, including researchers and students from statistics, and the health and social sciences. The wealth of examples makes this book an ideal reference for anyone involved in statistical modelling and analysis.

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Applied Bayesian Modelling

By Peter Congdon

Contributor Peter Congdon

Edition: illustrated, reprint

Published by John Wiley and Sons, 2003

ISBN 0471486957, 9780471486954

457 pages

This textbook on applied probability is intended for graduate students in applied mathematics, biostatistics, computational biology, computer science, physics, and statistics. It presupposes knowledge of multivariate calculus, linear algebra, ordinary differential equations, and elementary probability theory. Given these prerequisites, Applied Probability presents a unique blend of theory and applications, with special emphasis on mathematical modeling, computational techniques, and examples from the biological sciences.Chapter 1 reviews elementary probability and provides a brief survey of relevant results from measure theory. Chapter 2 is an extended essay on calculating expectations. Chapter 3 deals with probabilistic applications of convexity, inequalities, and optimization theory. Chapters 4 and 5 touch on combinatorics and combinatorial optimization. Chapters 6 through 11 present core material on stochastic processes. If supplemented with appropriate sections from Chapters 1 and 2, there is sufficient material here for a traditional semester-long course in stochastic processes covering the basics of Poisson processes, Markov chains, branching processes, martingales, and diffusion processes. Finally, Chapters 12 and 13 develop the Chen-Stein method of Poisson approximation and connections between probability and number theory.Kenneth Lange is Professor of Biomathematics and Human Genetics andChair of the Department of Human Genetics at the UCLA School of Medicine. He has held appointments at the University of New Hampshire, MIT, Harvard, and the University of Michigan. While at the University of Michigan, he was the Pharmacia & Upjohn Foundation Professor of Biostatistics. His research interests include human genetics, population modeling, biomedical imaging, computational statistics,and applied stochastic processes. Springer-Verlag published his booksNumerical Analysis for Statisticians and Mathematical and Statistical Methods for Genetic Analysis Second Edition, in 1999 and 2002, respectively.

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Applied Probability

By Kenneth Lange

Edition: illustrated

Published by Springer, 2003

ISBN 0387004254, 9780387004259

300 pages

Senior probabilists from around the world with widely differing specialities gave their visions of the state of their specialty, why they think it is important, and how they think it will develop innbsp;the new millenium. The volume includes papers given at a symposium at Columbia University in 1995, but papers from others not at the meeting were added to broaden the coverage of areas. All papers were refereed.

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Probability Towards 2000

By Luigi Accardi, C. C. Heyde

Edition: illustrated

Published by Springer, 1998

ISBN 0387984585, 9780387984582

356 pages

This text brings statistical tools to engineers and scientists who design and develop new products, new manufacturing systems and processes and who improve existing systems. Written by engineers for engineers, the examples and exercises are engineering-based, containing real data. And because computers are used to apply statistical methods to solve problems, output is presented from Statgraphics and SAS to illustrate what can be done with modern statistical software. Readers will master discrete and continuous random variables and probability distributions; point and interval estimation; testing hypotheses; simple and multiple linear regression; design of experiments; nonparametric statistics; and statistical quality control.

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Applied Statistics and Probability for Engineers

By Douglas C. Montgomery, George C. Runger

Edition: 2, illustrated, revised

Published by Wiley, 1999

ISBN 0471170275, 9780471170273

817 pages

With Montgomery and Runger's best-selling engineering statistics text, you can learn how to apply statistics to real engineering situations. The text shows you how to use statistical methods to design and develop new products, and new manufacturing systems and processes. You'll gain a better understanding of how these methods are used in everyday work, and get a taste of practical engineering experience through real-world, engineering-based examples and exercises.


Now revised, this Fourth Edition of Applied Statistics and Probability for Engineers features many new homework exercises, including a greater variation of problems and more computer problems.

Key Features
* The text treats all topics in a way that reflects today's engineering realities. In the probability chapters, the authors emphasize engineering-specific examples, rather than counting methods or artificial applications such as gambling.
* Examples and exercises throughout the text use real data and real engineering situations.
* Coverage of probability is lively and interesting. It is complete but concise so as not to take over the content of the entire text.
* Thorough coverage of regression modeling, design of engineering experiments, and statistical process control from experts in these topics makes the book especially useful as a reference.

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Applied Statistics and Probability for Engineers: Student Solutions Manual

By Douglas C. Montgomery, George C. Runger

Edition: 4, illustrated, revised

Published by John Wiley & Sons, Incorporated, 2006

ISBN 0470099402, 9780470099407

140 pages

Users of statistics in their professional lives and statistics students will welcome this concise, easy-to-use reference for basic statistics and probability. It contains all of the standardized statistical tables and formulas typically needed plus material on basic statistics topics, such as probability theory and distributions, regression, analysis of variance, nonparametric statistics, and statistical quality control. For each type of distribution the authors supply: ? definitions ? tables ? relationships with other distributions, including limiting forms ? statistical parameters, such as variance and generating functions ? a list of common problems involving the distribution Standard Probability and Statistics: Tables and Formulae also includes discussion of common statistical problems and supplies examples that show readers how to use the tables and formulae to get the solutions they need. With this handy reference, the focus can shift from rote learning and memorization to the concepts needed to use statistics efficiently and effectively.

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CRC Standard Probability and Statistics Tables and Formulae: Student Edition

By Stephen Kokoska, Daniel Zwillinger

Edition: illustrated

Published by CRC Press, 2000

ISBN 0849300266, 9780849300264

225 pages

Key words and phrases

Borel sets, Conditional Mathematical Expectations, elementary events, Law of Large, Markov chains, Conditional Expectations, converges in probability, probability space, theory of probability, probability theory, Stochastic Processes, meridian circle, Lebesgue Integrals, field of probability, Banach Space, NIKODYM, Stieltjes integral, Central Limit Theorem, finite fields, A. N. KOLMOGOROV

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Foundations of the Theory of Probability

By Andreĭ Nikolaevich Kolmogorov

Edition: 2

Published by Chelsea Pub. Co., 1956

84 pages

This textbook differs from others in the field in that it has been prepared very much with students and their needs in mind, having been classroom tested over many years. It is a true "learner's book" made for students who require a deeper understanding of probability and statistics. It presents the fundamentals of the subject along with concepts of probabilistic modelling, and the process of model selection, verification and analysis. Furthermore, the inclusion of more than 100 examples and 200 exercises (carefully selected from a wide range of topics), along with a solutions manual for instructors, means that this text is of real value to students and lecturers across a range of engineering disciplines. Key features: Presents the fundamentals in probability and statistics along with relevant applications. Explains the concept of probabilistic modelling and the process of model selection, verification and analysis. Definitions and theorems are carefully stated and topics rigorously treated. Includes a chapter on regression analysis. Covers design of experiments. Demonstrates practical problem solving throughout the book with numerous examples and exercises purposely selected from a variety of engineering fields. Includes an accompanying online Solutions Manual for instructors containing complete step-by-step solutions to all problems.

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Fundamentals of Probability and Statistics for Engineers

By T. T. Soong

Contributor T. T. Soong

Edition: illustrated

Published by John Wiley and Sons, 2004

ISBN 0470868147, 9780470868140

391 pages

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Introduction to Probability: Dimitri P. Bertsekas and John N. Tsitsiklis

By Dimitri P. Bertsekas, John N. Tsitsiklis

Contributor John N. Tsitsiklis

Published by Athena Scientific, 2002

ISBN 188652940X, 9781886529403

416 pages

Key words and phrases

reactive power, energy balances, wattmeters, thermal energy, enthalpy, objective function, Sankey diagrams, power factor, Flowchart, mathematical models, electric networks, FORTRAN, voltmeter, heat exchange, Romania, operational research, simplex algorithm, operating conditions, load curve, no-load

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Models of Real and Optimum Energy Balances

By A. Carabulea, Ion Gheorghe Carabogdan

Edition: revised

Published by Elsevier, 1990

Original from the University of Michigan

Digitized Dec 5, 2007

ISBN 0444988610, 9780444988614

381 pages

Key words and phrases

South Africa, 19th century, Spain, photosphere, World War II, Spacelab, solar wind, sulfuric acid, solar system, Sudan, Salyut, superconductivity, sunspots, helium, cosmonauts, Sweden, supernova, magnetic field, Argentina, Somali

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Academic American Encyclopedia

Contributor Inc Grolier

Published by Grolier Incorporated, 1994

Item notes: v.18

Original from the University of Michigan

Digitized Mar 13, 2006

ISBN 0717220532, 9780717220533

21 pages

This text is designed for an introductory probability course at the university level for undergraduates in mathematics, the physical and social sciences, engineering, and computer science. It presents a thorough treatment of probability 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 over 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.

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Introduction to Probability

By Charles Miller Grinstead, James Laurie Snell

Edition: 2

Published by AMS Bookstore, 1997

ISBN 0821807498, 9780821807491

510 pages

This book is a translation of the third edition of the highly successful German textbook "Stochastik." This new English edition presents the fundamental ideas and results of both probability theory and statistics, and comprises the material of a one-year course. The stochastic concepts, models and methods are motivated by examples and problems and then developed and analysed systematically.

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Stochastics: Introduction to Probability Theory and Statistics

By Hans-Otto Georgii

Translated by Hans-Otto Georgii, Marcel Ortgiese, Ellen Baake

Edition: illustrated

Published by Walter de Gruyter, 2008

ISBN 3110191458, 9783110191455

370 pages

This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises.

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Introduction to Statistical Pattern Recognition

By Keinosuke Fukunaga

Edition: 2, illustrated, revised

Published by Academic Press, 1990

ISBN 0122698517, 9780122698514

591 pages