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Mathematical Statistics With Applications In R

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Mathematical Statistics with Applications in R

Mathematical Statistics with Applications in R Book
Author : Kandethody M. Ramachandran,Chris P. Tsokos
Publisher : Elsevier
Release : 2014-09-14
ISBN : 012417132X
Language : En, Es, Fr & De

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Book Description :

Mathematical Statistics with Applications in R, Second Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining the discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem solving in a logical manner. This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students. Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies. Step-by-step procedure to solve real problems, making the topic more accessible Exercises blend theory and modern applications Practical, real-world chapter projects Provides an optional section in each chapter on using Minitab, SPSS and SAS commands Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods

Mathematical Statistics with Applications in R

Mathematical Statistics with Applications in R Book
Author : Kandethody M. Ramachandran,Chris P. Tsokos
Publisher : Academic Press
Release : 2020-05-14
ISBN : 0128178167
Language : En, Es, Fr & De

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Book Description :

Mathematical Statistics with Applications in R, Third Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods, such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem-solving in a logical manner. Step-by-step procedure to solve real problems make the topics very accessible. Presents step-by-step procedures to solve real problems, making each topic more accessible Provides updated application exercises in each chapter, blending theory and modern methods with the use of R Includes new chapters on Categorical Data Analysis and Extreme Value Theory with Applications Wide array coverage of ANOVA, Nonparametric, Bayesian and empirical methods

Probability and Mathematical Statistics Theory Applications and Practice in R

Probability and Mathematical Statistics  Theory  Applications  and Practice in R Book
Author : Mary C. Meyer
Publisher : SIAM
Release : 2019-06-24
ISBN : 1611975786
Language : En, Es, Fr & De

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Book Description :

This book develops the theory of probability and mathematical statistics with the goal of analyzing real-world data. Throughout the text, the R package is used to compute probabilities, check analytically computed answers, simulate probability distributions, illustrate answers with appropriate graphics, and help students develop intuition surrounding probability and statistics. Examples, demonstrations, and exercises in the R programming language serve to reinforce ideas and facilitate understanding and confidence. The book’s Chapter Highlights provide a summary of key concepts, while the examples utilizing R within the chapters are instructive and practical. Exercises that focus on real-world applications without sacrificing mathematical rigor are included, along with more than 200 figures that help clarify both concepts and applications. In addition, the book features two helpful appendices: annotated solutions to 700 exercises and a Review of Useful Math. Written for use in applied masters classes, Probability and Mathematical Statistics: Theory, Applications, and Practice in R is also suitable for advanced undergraduates and for self-study by applied mathematicians and statisticians and qualitatively inclined engineers and scientists.

Mathematical Statistics with Resampling and R

Mathematical Statistics with Resampling and R Book
Author : Laura M. Chihara,Tim C. Hesterberg
Publisher : John Wiley & Sons
Release : 2018-09-17
ISBN : 1119416523
Language : En, Es, Fr & De

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Book Description :

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.

Cluster Analysis for Applications

Cluster Analysis for Applications Book
Author : Michael R. Anderberg
Publisher : Academic Press
Release : 2014-05-10
ISBN : 1483191397
Language : En, Es, Fr & De

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Book Description :

Cluster Analysis for Applications deals with methods and various applications of cluster analysis. Topics covered range from variables and scales to measures of association among variables and among data units. Conceptual problems in cluster analysis are discussed, along with hierarchical and non-hierarchical clustering methods. The necessary elements of data analysis, statistics, cluster analysis, and computer implementation are integrated vertically to cover the complete path from raw data to a finished analysis. Comprised of 10 chapters, this book begins with an introduction to the subject of cluster analysis and its uses as well as category sorting problems and the need for cluster analysis algorithms. The next three chapters give a detailed account of variables and association measures, with emphasis on strategies for dealing with problems containing variables of mixed types. Subsequent chapters focus on the central techniques of cluster analysis with particular reference to computational considerations; interpretation of clustering results; and techniques and strategies for making the most effective use of cluster analysis. The final chapter suggests an approach for the evaluation of alternative clustering methods. The presentation is capped with a complete set of implementing computer programs listed in the Appendices to make the use of cluster analysis as painless and free of mechanical error as is possible. This monograph is intended for students and workers who have encountered the notion of cluster analysis.

Foundations and Applications of Statistics

Foundations and Applications of Statistics Book
Author : Randall Pruim
Publisher : American Mathematical Soc.
Release : 2018-04-04
ISBN : 1470428482
Language : En, Es, Fr & De

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Book Description :

Foundations and Applications of Statistics simultaneously emphasizes both the foundational and the computational aspects of modern statistics. Engaging and accessible, this book is useful to undergraduate students with a wide range of backgrounds and career goals. The exposition immediately begins with statistics, presenting concepts and results from probability along the way. Hypothesis testing is introduced very early, and the motivation for several probability distributions comes from p-value computations. Pruim develops the students' practical statistical reasoning through explicit examples and through numerical and graphical summaries of data that allow intuitive inferences before introducing the formal machinery. The topics have been selected to reflect the current practice in statistics, where computation is an indispensible tool. In this vein, the statistical computing environment R is used throughout the text and is integral to the exposition. Attention is paid to developing students' mathematical and computational skills as well as their statistical reasoning. Linear models, such as regression and ANOVA, are treated with explicit reference to the underlying linear algebra, which is motivated geometrically. Foundations and Applications of Statistics discusses both the mathematical theory underlying statistics and practical applications that make it a powerful tool across disciplines. The book contains ample material for a two-semester course in undergraduate probability and statistics. A one-semester course based on the book will cover hypothesis testing and confidence intervals for the most common situations. In the second edition, the R code has been updated throughout to take advantage of new R packages and to illustrate better coding style. New sections have been added covering bootstrap methods, multinomial and multivariate normal distributions, the delta method, numerical methods for Bayesian inference, and nonlinear least squares. Also, the use of matrix algebra has been expanded, but remains optional, providing instructors with more options regarding the amount of linear algebra required.

Mathematical Statistics

Mathematical Statistics Book
Author : Wiebe R. Pestman,Ivo B. Alberink
Publisher : Walter de Gruyter
Release : 1998-01-01
ISBN : 3110809346
Language : En, Es, Fr & De

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Book Description :

Download Mathematical Statistics book written by Wiebe R. Pestman,Ivo B. Alberink, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Mathematical Statistics with Resampling and R Probability with Applications and R Set

Mathematical Statistics with Resampling and R   Probability with Applications and R Set Book
Author : Laura M. Chihara,Tim C. Hesterberg,Robert P. Dobrow
Publisher : Wiley
Release : 2014-03-31
ISBN : 9781118947432
Language : En, Es, Fr & De

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Book Description :

This book bridges 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. This groundbreaking book shows how to apply modern resampling techniques to mathematical statistics. Extensively class-tested to ensure an accessible presentation, M"athematical Statistics with Resampling and R" utilizes the powerful and flexible computer language R to underscore the significance and benefits of modern resampling techniques. The book begins by introducing permutation tests and bootstrap methods, motivating classical inference methods. Striking a balance between theory, computing, and applications, the authors explore additional topics such as: Exploratory data analysis Calculation of sampling distributions The Central Limit Theorem Monte Carlo sampling Maximum likelihood estimation and properties of estimators Confidence intervals and hypothesis tests Regression Bayesian methods Throughout the book, case studies on diverse subjects such as flight delays, birth weights of babies, and telephone company repair times illustrate the relevance of the real-world applications of the discussed material. Key definitions and theorems of important probability distributions are collected at the end of the book, and a related website is also available, featuring additional material including data sets, R scripts, and helpful teaching hints. "Mathematical Statistics with Resampling and R" is an excellent book for courses on mathematical statistics at the upper-undergraduate and graduate levels. It also serves as a valuable reference for applied statisticians working in the areas of business, economics, biostatistics, and public health who utilize resampling methods in their everyday work.

Statistics for Engineering and the Sciences

Statistics for Engineering and the Sciences Book
Author : William Mendenhall,Terry Sincich
Publisher : Prentice Hall
Release : 2007
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

This text is designed for a two-semester introductory course in statistics for students majoring in engineering or any of the physical sciences. Inevitably, once these students graduate and are employed, they will be involved in the collection and analysis of data and will be required to think critically about the results. Consequently, they need to acquire knowledge of the basic concepts of data description and statistical inference and familiarity with statistical methods they are required to use on the job.

Soviet Union

Soviet Union Book
Author : Anonim
Publisher : Unknown
Release : 1965
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Soviet Union book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

An Introduction to Statistical Learning

An Introduction to Statistical Learning Book
Author : Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani
Publisher : Springer Science & Business Media
Release : 2013-06-24
ISBN : 1461471389
Language : En, Es, Fr & De

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Book Description :

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Probability Theory and Mathematical Statistics with Applications

Probability Theory and Mathematical Statistics with Applications Book
Author : Wilfried Grossmann
Publisher : Unknown
Release : 1988
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Probability Theory and Mathematical Statistics with Applications book written by Wilfried Grossmann, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Scientific Research in British Universities and Colleges

Scientific Research in British Universities and Colleges Book
Author : Anonim
Publisher : Unknown
Release : 1971
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Scientific Research in British Universities and Colleges book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Practical Statistics by Example Using Microsoft Excel

Practical Statistics by Example Using Microsoft Excel Book
Author : Terry Sincich,David M. Levine,David Stephan
Publisher : Unknown
Release : 1999
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

This manual includes an Excel primer providing basic instructions on using Windows and Excel. Excel Tutorials appear at the end of pertinent chapters. Self-test questions, key terms, formulas and symbols are included.

Current Index to Statistics Applications Methods and Theory

Current Index to Statistics  Applications  Methods and Theory Book
Author : Anonim
Publisher : Unknown
Release : 1993
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Current Index to Statistics Applications Methods and Theory book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

An Introduction to Statistical Inference and Its Applications with R

An Introduction to Statistical Inference and Its Applications with R Book
Author : Michael W. Trosset
Publisher : CRC Press
Release : 2009-06-23
ISBN : 1584889489
Language : En, Es, Fr & De

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Book Description :

Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition of the methods of statistical inference for students who are comfortable with mathematical notation. Numerous examples, case studies, and exercises are included. R is used to simplify computation, create figures

Who s who in Technology Today

Who s who in Technology Today Book
Author : Anonim
Publisher : Unknown
Release : 1981
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Who s who in Technology Today book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Probability and Statistics for Data Science

Probability and Statistics for Data Science Book
Author : Norman Matloff
Publisher : CRC Press
Release : 2019-06-21
ISBN : 0429687125
Language : En, Es, Fr & De

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Book Description :

Probability and Statistics for Data Science: Math + R + Data covers "math stat"—distributions, expected value, estimation etc.—but takes the phrase "Data Science" in the title quite seriously: * Real datasets are used extensively. * All data analysis is supported by R coding. * Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks. * Leads the student to think critically about the "how" and "why" of statistics, and to "see the big picture." * Not "theorem/proof"-oriented, but concepts and models are stated in a mathematically precise manner. Prerequisites are calculus, some matrix algebra, and some experience in programming. Norman Matloff is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics in 2017. He is a recipient of his university's Distinguished Teaching Award.

Basics of Modern Mathematical Statistics

Basics of Modern Mathematical Statistics Book
Author : Wolfgang Karl Härdle,Vladimir Spokoiny,Vladimir Panov,Weining Wang
Publisher : Springer Science & Business Media
Release : 2013-11-08
ISBN : 3642368506
Language : En, Es, Fr & De

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Book Description :

​The complexity of today’s statistical data calls for modern mathematical tools. Many fields of science make use of mathematical statistics and require continuous updating on statistical technologies. Practice makes perfect, since mastering the tools makes them applicable. Our book of exercises and solutions offers a wide range of applications and numerical solutions based on R. In modern mathematical statistics, the purpose is to provide statistics students with a number of basic exercises and also an understanding of how the theory can be applied to real-world problems. The application aspect is also quite important, as most previous exercise books are mostly on theoretical derivations. Also we add some problems from topics often encountered in recent research papers. The book was written for statistics students with one or two years of coursework in mathematical statistics and probability, professors who hold courses in mathematical statistics, and researchers in other fields who would like to do some exercises on math statistics.