## Introduction to Probability and Mathematical Statistics

**Author**: Lee J. Bain,Max Engelhardt

**Publisher:**Duxbury Press

**ISBN:**9780534380205

**Category:**Mathematics

**Page:**644

**View:**2613

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The Second Edition of INTRODUCTION TO PROBABILITY AND MATHEMATICAL STATISTICS focuses on developing the skills to build probability (stochastic) models. Lee J. Bain and Max Engelhardt focus on the mathematical development of the subject, with examples and exercises oriented toward applications.

## Introduction to Probability

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

**Publisher:**American Mathematical Soc.

**ISBN:**0821894145

**Category:**Probabilities

**Page:**510

**View:**3963

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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

## Matrices with Applications in Statistics

**Author**: Franklin A. Graybill

**Publisher:**Duxbury Press

**ISBN:**9780534401313

**Category:**Mathematics

**Page:**461

**View:**6038

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Part of the Duxbury Classic series, Franklin A. Graybill’s MATRICES WITH APPLICATIONS TO STATISTICS focuses primarily on matrices as they relate to areas of multivariate analysis and the linear model. This seminal work is a time tested, authoritative resource for both students and researchers.

## Models for Probability and Statistical Inference

*Theory and Applications*

**Author**: James H. Stapleton

**Publisher:**John Wiley & Sons

**ISBN:**9780470183403

**Category:**Mathematics

**Page:**512

**View:**6643

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This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression. Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.

## Introduction to Stochastic Processes, Second Edition

**Author**: Gregory F. Lawler

**Publisher:**CRC Press

**ISBN:**9781584886518

**Category:**Mathematics

**Page:**248

**View:**3195

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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.

## Mathematical Statistics with Resampling and R

**Author**: Laura M. Chihara,Tim C. Hesterberg

**Publisher:**John Wiley & Sons

**ISBN:**1119416523

**Category:**Mathematics

**Page:**560

**View:**2241

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This thoroughly updated second edition combines the latest software applications with the benefits of modern resampling techniques Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. The second edition of Mathematical Statistics with Resampling and R combines modern resampling techniques and mathematical statistics. This book has been classroom-tested to ensure an accessible presentation, uses the powerful and flexible computer language R for data analysis and explores the benefits of modern resampling techniques. This book offers an introduction to permutation tests and bootstrap methods that can serve to motivate classical inference methods. The book strikes a balance between theory, computing, and applications, and the new edition explores additional topics including consulting, paired t test, ANOVA and Google Interview Questions. Throughout the book, new and updated case studies are included representing a diverse range of subjects such as flight delays, birth weights of babies, and telephone company repair times. These illustrate the relevance of the real-world applications of the material. This new edition: • Puts the focus on statistical consulting that emphasizes giving a client an understanding of data and goes beyond typical expectations • Presents new material on topics such as the paired t test, Fisher's Exact Test and the EM algorithm • Offers a new section on "Google Interview Questions" that illustrates statistical thinking • Provides a new chapter on ANOVA • Contains more exercises and updated case studies, data sets, and R code Written for undergraduate students in a mathematical statistics course as well as practitioners and researchers, the second edition of Mathematical Statistics with Resampling and R presents a revised and updated guide for applying the most current resampling techniques to mathematical statistics.

## Mathematical Statistics and Data Analysis

**Author**: John A. Rice

**Publisher:**Cengage Learning

**ISBN:**0534399428

**Category:**Mathematics

**Page:**688

**View:**5702

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This is the first text in a generation to re-examine the purpose of the mathematical statistics course. The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts that are set in abstract settings. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

## Regression Analysis

**Author**: Rudolf J. Freund,William J. Wilson,Ping Sa

**Publisher:**Elsevier

**ISBN:**0080522971

**Category:**Mathematics

**Page:**480

**View:**1412

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Regression Analysis provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation, and have some appreciation of what constitutes good experimental design. Examples and exercises contain real data and graphical illustration for ease of interpretation Outputs from SAS 7, SPSS 7, Excel, and Minitab are used for illustration, but any major statistical software package will work equally well

## Statistical Inference

**Author**: George Casella,Roger L. Berger

**Publisher:**Duxbury Press

**ISBN:**N.A

**Category:**Mathematics

**Page:**660

**View:**5457

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Casella and Berger's new edition builds the theoretical statistics from the first principals of probability theory. Thoroughly and completely, the authors start with the basics of probability and then move on to develop the theory of statistical inference using techniques, definitions, and statistical concepts.

## Statistical Computing with R

**Author**: Maria L. Rizzo

**Publisher:**CRC Press

**ISBN:**1498786596

**Category:**Mathematics

**Page:**416

**View:**2188

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Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve statistical problems, making the versatile R language an ideal computing environment for these fields. One of the first books on these topics to feature R, Statistical Computing with R covers the traditional core material of computational statistics, with an emphasis on using the R language via an examples-based approach. Suitable for an introductory course in computational statistics or for self-study, it includes R code for all examples and R notes to help explain the R programming concepts. After an overview of computational statistics and an introduction to the R computing environment, the book reviews some basic concepts in probability and classical statistical inference. Each subsequent chapter explores a specific topic in computational statistics. These chapters cover the simulation of random variables from probability distributions, the visualization of multivariate data, Monte Carlo integration and variance reduction methods, Monte Carlo methods in inference, bootstrap and jackknife, permutation tests, Markov chain Monte Carlo (MCMC) methods, and density estimation. The final chapter presents a selection of examples that illustrate the application of numerical methods using R functions. Focusing on implementation rather than theory, this text serves as a balanced, accessible introduction to computational statistics and statistical computing.

## Mathematics and Climate

**Author**: Hans Kaper,Hans Engler

**Publisher:**SIAM

**ISBN:**1611972612

**Category:**Science

**Page:**326

**View:**9626

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Mathematics and Climate is a timely textbook aimed at students and researchers in mathematics and statistics who are interested in current issues of climate science, as well as at climate scientists who wish to become familiar with qualitative and quantitative methods of mathematics and statistics. The authors emphasize conceptual models that capture important aspects of Earth's climate system and present the mathematical and statistical techniques that can be applied to their analysis. Topics from climate science include the Earth?s energy balance, temperature distribution, ocean circulation patterns such as El Ni?o?Southern Oscillation, ice caps and glaciation periods, the carbon cycle, and the biological pump. Among the mathematical and statistical techniques presented in the text are dynamical systems and bifurcation theory, Fourier analysis, conservation laws, regression analysis, and extreme value theory. The following features make Mathematics and Climate a valuable teaching resource: issues of current interest in climate science and sustainability are used to introduce the student to the methods of mathematics and statistics; the mathematical sophistication increases as the book progresses and topics can thus be selected according to interest and level of knowledge; each chapter ends with a set of exercises that reinforce or enhance the material presented in the chapter and stimulate critical thinking and communication skills; and the book contains an extensive list of references to the literature, a glossary of terms for the nontechnical reader, and a detailed index.

## Introduction to Applied Econometrics

**Author**: Kenneth G. Stewart

**Publisher:**South-Western Pub

**ISBN:**9780534369163

**Category:**Business & Economics

**Page:**913

**View:**5047

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You'll find the "econ" back in econometrics with INTRODUCTION TO APPLIED ECONOMETRICS and its accompanying CD.. You'll have the opportunity to replicate classic empirical findings using original data sets and will develop an understanding of the relevance of economic theory to empirical analysis. The author integrates classic empirical examples and applications and builds toward a self-contained four-chapter introduction to time series analysis. The CD includes data sets formatted for STATA, Eviews, Excel, Minitab, SAS and ASCII, as well as an appendix presenting multiple regression in matrix form and another on treating portfolio theory and the capital asset pricing model.

## Numerical Methods

*Design, Analysis, and Computer Implementation of Algorithms*

**Author**: Anne Greenbaum,Timothy P. Chartier

**Publisher:**Princeton University Press

**ISBN:**1400842670

**Category:**Mathematics

**Page:**464

**View:**9943

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Numerical Methods provides a clear and concise exploration of standard numerical analysis topics, as well as nontraditional ones, including mathematical modeling, Monte Carlo methods, Markov chains, and fractals. Filled with appealing examples that will motivate students, the textbook considers modern application areas, such as information retrieval and animation, and classical topics from physics and engineering. Exercises use MATLAB and promote understanding of computational results. The book gives instructors the flexibility to emphasize different aspects--design, analysis, or computer implementation--of numerical algorithms, depending on the background and interests of students. Designed for upper-division undergraduates in mathematics or computer science classes, the textbook assumes that students have prior knowledge of linear algebra and calculus, although these topics are reviewed in the text. Short discussions of the history of numerical methods are interspersed throughout the chapters. The book also includes polynomial interpolation at Chebyshev points, use of the MATLAB package Chebfun, and a section on the fast Fourier transform. Supplementary materials are available online. Clear and concise exposition of standard numerical analysis topics Explores nontraditional topics, such as mathematical modeling and Monte Carlo methods Covers modern applications, including information retrieval and animation, and classical applications from physics and engineering Promotes understanding of computational results through MATLAB exercises Provides flexibility so instructors can emphasize mathematical or applied/computational aspects of numerical methods or a combination Includes recent results on polynomial interpolation at Chebyshev points and use of the MATLAB package Chebfun Short discussions of the history of numerical methods interspersed throughout Supplementary materials available online

## Tools and Algorithms for the Construction and Analysis of Systems

*18th International Conference, TACAS 2012, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2012, Tallinn, Estonia, March 24 -- April 1, 2012, Proceedings*

**Author**: Cormac Flanagan,Barbara König

**Publisher:**Springer

**ISBN:**3642287565

**Category:**Computers

**Page:**560

**View:**9840

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This book constitutes the proceedings of the 18th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2012, held as part of the joint European Conference on Theory and Practice of Software, ETAPS 2012, which took place in Tallinn, Estonia, in March/April 2012. The 25 research papers, 2 case study papers, 3 regular tool papers, and 6 tool demonstrations papers presented in this book were carefully reviewed and selected from a total of 147 submissions. The papers are organized in topical sections named: SAT and SMT based methods; automata; model checking; case studies; memory models and termination; internet protocol verification; stochastic model checking; synthesis; provers and analysis techniques; tool demonstrations; and competition on software verification.

## Classical and Modern Regression with Applications

**Author**: Raymond H. Myers

**Publisher:**Duxbury Press

**ISBN:**9780534380168

**Category:**Mathematics

**Page:**488

**View:**2550

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Regression analysis is a vitally important statistical tool, with major advancements made by both practical data analysts and statistical theorists. In CLASSICAL AND MODERN REGRESSION WITH APPLICATIONS, Second Edition, Raymond H. Myers provides a solid foundation in classical regression, while introducing modern techniques. Throughout the text, a broad spectrum of applications are included from the physical sciences, engineering, biology, management, and economics.

## Introduction to Probability and Its Applications

**Author**: Richard Scheaffer,Linda Young

**Publisher:**Cengage Learning

**ISBN:**0534386717

**Category:**Mathematics

**Page:**480

**View:**2205

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This text focuses on the utility of probability in solving real-world problems for students in a one-semester calculus-based probability course. Theory is developed to a practical degree and grounded in discussion of its practical uses in solving real-world problems. Numerous applications using up-to-date real data in engineering and the life, social, and physical sciences illustrate and motivate the many ways probability affects our lives. The text’s accessible presentation carefully progresses from routine to more difficult problems to suit students of different backgrounds, and carefully explains how and where to apply methods. Students going on to more advanced courses in probability and statistics will gain a solid background in fundamental concepts and theory, while students who must apply probability to their courses engineering and the sciences will develop a working knowledge of the subject and appreciation of its practical power. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

## Introduction to Probability and Statistics

**Author**: William Mendenhall,Robert J. Beaver,Barbara M. Beaver

**Publisher:**Cengage Learning

**ISBN:**1133711677

**Category:**Mathematics

**Page:**744

**View:**6043

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Used by hundreds of thousands of students since its first edition, INTRODUCTION TO PROBABILITY AND STATISTICS, Fourteenth Edition, continues to blend the best of its proven, error-free coverage with new innovations. Written for the higher end of the traditional introductory statistics market, the book takes advantage of modern technology--including computational software and interactive visual tools--to facilitate statistical reasoning as well as the interpretation of statistical results. In addition to showing how to apply statistical procedures, the authors explain how to describe real sets of data meaningfully, what the statistical tests mean in terms of their practical applications, how to evaluate the validity of the assumptions behind statistical tests, and what to do when statistical assumptions have been violated. The new edition retains the statistical integrity, examples, exercises, and exposition that have made this text a market leader--and builds upon this tradition of excellence with new technology integration. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

## Applied Nonparametric Statistics

**Author**: Wayne W. Daniel

**Publisher:**Brooks/Cole

**ISBN:**9780534381943

**Category:**Mathematics

**Page:**635

**View:**650

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This book covers the most commonly used nonparametric statistical techniques by emphasizing applications rather than theory. Exercises and examples are drawn from various disciplines including agriculture, biology, sociology, education, psychology, medicine, business, geology, and anthropology. The applications of techniques are presented in a step-by-step format that is repeated for all illustrative examples. Concepts are reinforced with many references to statistical literature to show the relevance to real-world problems. Chapters contain references of available computer programs and software packages that apply to methods presented in the book.

## Fundamental Concepts in the Design of Experiments

**Author**: Charles Robert Hicks,Kenneth V. Turner

**Publisher:**Oxford University Press, USA

**ISBN:**9780195122732

**Category:**Mathematics

**Page:**565

**View:**4022

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students valuable practice with real data and problem solving.

## Introduction to Regression Modeling

**Author**: Bovas Abraham,Johannes Ledolter

**Publisher:**Duxbury Press

**ISBN:**9780534420758

**Category:**Mathematics

**Page:**433

**View:**1097

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Looking for an easy-to-understand text to guide you through the tough topic of regression modeling? INTRODUCTION TO REGRESSION MODELING (WITH CD-ROM) offers a blend of theory and regression applications and will give you the practice you need to tackle this subject through exercises, case studies. and projects that have you identify a problem of interest and collect data relevant to the problem's solution. The book goes beyond linear regression by covering nonlinear models, regression models with time series errors, and logistic and Poisson regression models.