Introduction to Statistics Through Resampling Methods and R/S-PLUS

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 0471722499
Total Pages : 244 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Introduction to Statistics Through Resampling Methods and R/S-PLUS by : Phillip I. Good

Download or read book Introduction to Statistics Through Resampling Methods and R/S-PLUS written by Phillip I. Good and published by John Wiley & Sons. This book was released on 2012-01-20 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stimulate learning through discovery With its emphasis on the discovery method, this book allows readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers will quickly master and learn to apply statistical methods, such as bootstrap, decision trees, and permutations, to better characterize, report, test, and classify their research findings. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research, including: Tests and estimation procedures for one, two, and multiple samples Model building Multivariate analysis Complex experimental design Throughout the text, the R programming language is used to illustrate new concepts and assist readers in completing exercises. Readers may download the freely available R programming language from the Internet or take advantage of the menu-driven S-PLUS® program. Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. All the pedagogical tools needed to facilitate quick learning are provided: More than two hundred exercises scattered throughout the text stimulate readers' thinking and actively engage them in applying their newfound skills Companion FTP site provides access to all data sets and programs discussed in the text Dozens of thought-provoking questions in the final chapter, Problem Solving, assist readers in applying statistics to address real-life problems Instructor's manual provides answers to exercises Helpful appendices include an introduction to S-PLUS® features This text serves as an excellent introduction to statistics for students in all disciplines. The accessible style and focus on real-life problem solving are perfectly suited for both students and practitioners.

Introduction to Statistics Through Resampling Methods and R

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 1118428218
Total Pages : 224 pages
Book Rating : 4.1/5 (184 download)

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Book Synopsis Introduction to Statistics Through Resampling Methods and R by : Phillip I. Good

Download or read book Introduction to Statistics Through Resampling Methods and R written by Phillip I. Good and published by John Wiley & Sons. This book was released on 2013-02-11 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: A highly accessible alternative approach to basic statistics Praise for the First Edition: "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician."—Technometrics Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the understanding of descriptive statistics, estimation, hypothesis testing, and model building. The book emphasizes the discovery method, enabling readers to ascertain solutions on their own rather than simply copy answers or apply a formula by rote. The Second Edition utilizes the R programming language to simplify tedious computations, illustrate new concepts, and assist readers in completing exercises. The text facilitates quick learning through the use of: More than 250 exercises—with selected "hints"—scattered throughout to stimulate readers' thinking and to actively engage them in applying their newfound skills An increased focus on why a method is introduced Multiple explanations of basic concepts Real-life applications in a variety of disciplines Dozens of thought-provoking, problem-solving questions in the final chapter to assist readers in applying statistics to real-life applications Introduction to Statistics through Resampling Methods and R, Second Edition is an excellent resource for students and practitioners in the fields of agriculture, astrophysics, bacteriology, biology, botany, business, climatology, clinical trials, economics, education, epidemiology, genetics, geology, growth processes, hospital administration, law, manufacturing, marketing, medicine, mycology, physics, political science, psychology, social welfare, sports, and toxicology who want to master and learn to apply statistical methods.

Common Errors in Statistics (and How to Avoid Them), Third Edition and Introduction to Statistics Through Resampling Methods and R/S-PLUS Set

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Author :
Publisher : Wiley
ISBN 13 : 9780470555798
Total Pages : 0 pages
Book Rating : 4.5/5 (557 download)

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Book Synopsis Common Errors in Statistics (and How to Avoid Them), Third Edition and Introduction to Statistics Through Resampling Methods and R/S-PLUS Set by : Phillip I. Good

Download or read book Common Errors in Statistics (and How to Avoid Them), Third Edition and Introduction to Statistics Through Resampling Methods and R/S-PLUS Set written by Phillip I. Good and published by Wiley. This book was released on 2009-07-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This set features: Common Errors in Statistics (and How to Avoid Them), Third Edition by Phillip I. Good and James W. Hardin (978-0-470-45798-6) and Introduction to Statistics Through Resampling Methods and R/S-PLUS (978-0-471-71575-7)

Common Errors in Statistics (and How to Avoid Them), 2nd Edition + Introduction to Statistics Through Resampling Methods and Microsoft Office Excel

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Author :
Publisher : Wiley-Interscience
ISBN 13 : 9780470388105
Total Pages : 0 pages
Book Rating : 4.3/5 (881 download)

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Book Synopsis Common Errors in Statistics (and How to Avoid Them), 2nd Edition + Introduction to Statistics Through Resampling Methods and Microsoft Office Excel by : Phillip I. Good

Download or read book Common Errors in Statistics (and How to Avoid Them), 2nd Edition + Introduction to Statistics Through Resampling Methods and Microsoft Office Excel written by Phillip I. Good and published by Wiley-Interscience. This book was released on 2008-03-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This set contains: 9780471794318 Common Errors in Statistics (and How to Avoid Them), 2nd Edition and 9780471715757 Introduction to Statistics Through Resampling Methods and R/S Plus?? both by Phillip I. Good and James W. Hardin.

Mathematical Statistics with Resampling and R

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Publisher : John Wiley & Sons
ISBN 13 : 1118518950
Total Pages : 432 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Mathematical Statistics with Resampling and R by : Laura M. Chihara

Download or read book Mathematical Statistics with Resampling and R written by Laura M. Chihara and published by John Wiley & Sons. This book was released on 2012-09-05 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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, Mathematical 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.

Tracking Environmental Change Using Lake Sediments

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Publisher : Springer Science & Business Media
ISBN 13 : 9400727445
Total Pages : 751 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Tracking Environmental Change Using Lake Sediments by : John B.H. Birks

Download or read book Tracking Environmental Change Using Lake Sediments written by John B.H. Birks and published by Springer Science & Business Media. This book was released on 2012-04-08 with total page 751 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical and statistical methods have rapidly become part of a palaeolimnologist’s tool-kit. They are used to explore and summarise complex data, reconstruct past environmental variables from fossil assemblages, and test competing hypotheses about the causes of observed changes in lake biota through history. This book brings together a wide array of numerical and statistical techniques currently available for use in palaeolimnology and other branches of palaeoecology. ​ Visit http://extras.springer.com the Springer's Extras website to view data-sets, figures, software, and R scripts used or mentioned in this book.

Tracking Environmental Change Using Lake Sediments

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 9400727453
Total Pages : 751 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Tracking Environmental Change Using Lake Sediments by : H. John B. Birks

Download or read book Tracking Environmental Change Using Lake Sediments written by H. John B. Birks and published by Springer Science & Business Media. This book was released on 2012-04-06 with total page 751 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical and statistical methods have rapidly become part of a palaeolimnologist’s tool-kit. They are used to explore and summarise complex data, reconstruct past environmental variables from fossil assemblages, and test competing hypotheses about the causes of observed changes in lake biota through history. This book brings together a wide array of numerical and statistical techniques currently available for use in palaeolimnology and other branches of palaeoecology. ​ Visit http://extras.springer.com the Springer's Extras website to view data-sets, figures, software, and R scripts used or mentioned in this book.

Introductory Applied Statistics

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Publisher : Springer Nature
ISBN 13 : 3031277414
Total Pages : 197 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Introductory Applied Statistics by : Bruce Blaine

Download or read book Introductory Applied Statistics written by Bruce Blaine and published by Springer Nature. This book was released on 2023-05-05 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an introduction to applied statistics through data analysis, integrating statistical computing methods. It covers robust and non-robust descriptive statistics used in each of four bivariate statistical models that are commonly used in research: ANOVA, proportions, regression, and logistic. The text teaches statistical inference principles using resampling methods (such as randomization and bootstrapping), covering methods for hypothesis testing and parameter estimation. These methods are applied to each statistical model introduced in preceding chapters. Data analytic examples are used to teach statistical concepts throughout, and students are introduced to the R packages and functions required for basic data analysis in each of the four models. The text also includes introductory guidance to the fundamentals of data wrangling, as well as examples of write-ups so that students can learn how to communicate findings. Each chapter includes problems for practice or assessment. Supplemental instructional videos are also available as an additional aid to instructors, or as a general resource to students. This book is intended for an introductory or basic statistics course with an applied focus, or an introductory analytics course, at the undergraduate level in a two-year or four-year institution. This can be used for students with a variety of disciplinary backgrounds, from business, to the social sciences, to medicine. No sophisticated mathematical background is required.

Permutation Tests for Complex Data

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Publisher : John Wiley & Sons
ISBN 13 : 9780470689523
Total Pages : 448 pages
Book Rating : 4.6/5 (895 download)

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Book Synopsis Permutation Tests for Complex Data by : Fortunato Pesarin

Download or read book Permutation Tests for Complex Data written by Fortunato Pesarin and published by John Wiley & Sons. This book was released on 2010-02-25 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex multivariate testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. As a result, modern statistics needs permutation testing for complex data with low sample size and many variables, especially in observational studies. The Authors give a general overview on permutation tests with a focus on recent theoretical advances within univariate and multivariate complex permutation testing problems, this book brings the reader completely up to date with today’s current thinking. Key Features: Examines the most up-to-date methodologies of univariate and multivariate permutation testing. Includes extensive software codes in MATLAB, R and SAS, featuring worked examples, and uses real case studies from both experimental and observational studies. Includes a standalone free software NPC Test Release 10 with a graphical interface which allows practitioners from every scientific field to easily implement almost all complex testing procedures included in the book. Presents and discusses solutions to the most important and frequently encountered real problems in multivariate analyses. A supplementary website containing all of the data sets examined in the book along with ready to use software codes. Together with a wide set of application cases, the Authors present a thorough theory of permutation testing both with formal description and proofs, and analysing real case studies. Practitioners and researchers, working in different scientific fields such as engineering, biostatistics, psychology or medicine will benefit from this book.

Nonparametric Statistical Tests

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Author :
Publisher : CRC Press
ISBN 13 : 1439867046
Total Pages : 247 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Nonparametric Statistical Tests by : Markus Neuhauser

Download or read book Nonparametric Statistical Tests written by Markus Neuhauser and published by CRC Press. This book was released on 2011-12-19 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. Th

Resampling Methods

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Publisher : Springer Science & Business Media
ISBN 13 : 1475730497
Total Pages : 281 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Resampling Methods by : Phillip I. Good

Download or read book Resampling Methods written by Phillip I. Good and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: "...the author has packaged an excellent and modern set of topics around the development and use of quantitative models...the author has the capability to work at a more modest level. He does that very effectively in this 2nd Edition... If you need to learn about resampling, this book would be a good place to start." -- Technometrics This work is a practical, table-free introduction to data analysis using the bootstrap, cross-validation, and permutation tests; new to the second edition are several additional examples and a chapter dedicated to regression, data mining techniques, and their limitations. The book’s many exercises, practical data sets, and use of free shareware make it an essential resource for students and teachers, as well as industrial statisticians, consultants, and research professionals.

Probability and Statistical Inference

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Publisher : John Wiley & Sons
ISBN 13 : 1119243823
Total Pages : 592 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Probability and Statistical Inference by : Robert Bartoszynski

Download or read book Probability and Statistical Inference written by Robert Bartoszynski and published by John Wiley & Sons. This book was released on 2020-12-09 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Updated classic statistics text, with new problems and examples Probability and Statistical Inference, Third Edition helps students grasp essential concepts of statistics and its probabilistic foundations. This book focuses on the development of intuition and understanding in the subject through a wealth of examples illustrating concepts, theorems, and methods. The reader will recognize and fully understand the why and not just the how behind the introduced material. In this Third Edition, the reader will find a new chapter on Bayesian statistics, 70 new problems and an appendix with the supporting R code. This book is suitable for upper-level undergraduates or first-year graduate students studying statistics or related disciplines, such as mathematics or engineering. This Third Edition: Introduces an all-new chapter on Bayesian statistics and offers thorough explanations of advanced statistics and probability topics Includes 650 problems and over 400 examples - an excellent resource for the mathematical statistics class sequence in the increasingly popular "flipped classroom" format Offers students in statistics, mathematics, engineering and related fields a user-friendly resource Provides practicing professionals valuable insight into statistical tools Probability and Statistical Inference offers a unique approach to problems that allows the reader to fully integrate the knowledge gained from the text, thus, enhancing a more complete and honest understanding of the topic.

Resampling Methods

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Publisher : Springer Science & Business Media
ISBN 13 : 081764444X
Total Pages : 229 pages
Book Rating : 4.8/5 (176 download)

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Book Synopsis Resampling Methods by : Phillip I. Good

Download or read book Resampling Methods written by Phillip I. Good and published by Springer Science & Business Media. This book was released on 2006-12-31 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thoroughly revised and expanded third edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. Only requiring minimal mathematics beyond algebra, it provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware. New to the third edition are additional program listings and screen shots of C++, CART, Blossom, Box Sampler (an Excel add-in), EViews, MATLAB, R, Resampling Stats, SAS macros, S-Plus, Stata, or StatXact, which accompany each resampling procedure. A glossary and solutions to selected exercises have also been added. With its accessible style and intuitive topic development, the book is an excellent basic resource for the power, simplicity, and versatility of resampling methods. It is an essential resource for statisticians, biostatisticians, statistical consultants, students, and research professionals in the biological, physical, and social sciences, engineering, and technology.

Artificial Intelligence Methods in the Environmental Sciences

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Publisher : Springer Science & Business Media
ISBN 13 : 1402091192
Total Pages : 418 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Artificial Intelligence Methods in the Environmental Sciences by : Sue Ellen Haupt

Download or read book Artificial Intelligence Methods in the Environmental Sciences written by Sue Ellen Haupt and published by Springer Science & Business Media. This book was released on 2008-11-28 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.

Handbook of Educational Psychology

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Author :
Publisher : Routledge
ISBN 13 : 1135283516
Total Pages : 2419 pages
Book Rating : 4.1/5 (352 download)

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Book Synopsis Handbook of Educational Psychology by : Patricia A. Alexander

Download or read book Handbook of Educational Psychology written by Patricia A. Alexander and published by Routledge. This book was released on 2012-11-12 with total page 2419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sponsored by Division 15 of APA, the second edition of this groundbreaking book has been expanded to 41 chapters that provide unparalleled coverage of this far-ranging field. Internationally recognized scholars contribute up-to-date reviews and critical syntheses of the following areas: foundations and the future of educational psychology, learners’ development, individual differences, cognition, motivation, content area teaching, socio-cultural perspectives on teaching and learning, teachers and teaching, instructional design, teacher assessment, and modern perspectives on research methodologies, data, and data analysis. New chapters cover topics such as adult development, self-regulation, changes in knowledge and beliefs, and writing. Expanded treatment has been given to cognition, motivation, and new methodologies for gathering and analyzing data. The Handbook of Educational Psychology, Second Edition provides an indispensable reference volume for scholars, teacher educators, in-service practitioners, policy makers and the academic libraries serving these audiences. It is also appropriate for graduate level courses devoted to the study of educational psychology.

An Introduction to Statistical Learning

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Publisher : Springer Nature
ISBN 13 : 3031387473
Total Pages : 617 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis An Introduction to Statistical Learning by : Gareth James

Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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, marketing, and 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, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

Comparing Groups

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Publisher : John Wiley & Sons
ISBN 13 : 111806366X
Total Pages : 332 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis Comparing Groups by : Andrew S. Zieffler

Download or read book Comparing Groups written by Andrew S. Zieffler and published by John Wiley & Sons. This book was released on 2011-07-08 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on guide to using R to carry out key statisticalpractices in educational and behavioral sciencesresearch Computing has become an essential part of the day-to-daypractice of statistical work, broadening the types of questionsthat can now be addressed by research scientists applying newlyderived data analytic techniques. Comparing Groups:Randomization and Bootstrap Methods Using R emphasizes thedirect link between scientific research questions and dataanalysis. Rather than relying on mathematical calculations, thisbook focus on conceptual explanations and the use of statisticalcomputing in an effort to guide readers through the integration ofdesign, statistical methodology, and computation to answer specificresearch questions regarding group differences. Utilizing the widely-used, freely accessible R software, theauthors introduce a modern approach to promote methods that providea more complete understanding of statistical concepts. Following anintroduction to R, each chapter is driven by a research question,and empirical data analysis is used to provide answers to thatquestion. These examples are data-driven inquiries that promoteinteraction between statistical methods and ideas and computerapplication. Computer code and output are interwoven in the book toillustrate exactly how each analysis is carried out and how outputis interpreted. Additional topical coverage includes: Data exploration of one variable and multivariate data Comparing two groups and many groups Permutation tests, randomization tests, and the independentsamples t-Test Bootstrap tests and bootstrap intervals Interval estimates and effect sizes Throughout the book, the authors incorporate data fromreal-world research studies as well aschapter problems that providea platform to perform data analyses. A related Web site features acomplete collection of the book's datasets along with theaccompanying codebooks and the R script files and commands,allowing readers to reproduce the presented output and plots. Comparing Groups: Randomization and Bootstrap Methods UsingR is an excellent book for upper-undergraduate and graduatelevel courses on statistical methods, particularlyin theeducational and behavioral sciences. The book also serves as avaluable resource for researchers who need a practical guide tomodern data analytic and computational methods.