Introduction To Statistics Through Resampling Methods And R S Plus

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

Phillip I. Good
Introduction to Statistics Through Resampling Methods and R S PLUS Book PDF

Author : Phillip I. Good
Publisher : John Wiley & Sons
Page : 244 pages
File Size : 55,5 Mb
Release : 2012-01-20
Category : Mathematics
ISBN : 9780471722496

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

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

Phillip I. Good
Introduction to Statistics Through Resampling Methods and R Book PDF

Author : Phillip I. Good
Publisher : John Wiley & Sons
Page : 224 pages
File Size : 44,7 Mb
Release : 2013-02-11
Category : Mathematics
ISBN : 9781118428214

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Introduction to Statistics Through Resampling Methods and R by Phillip I. Good Pdf

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

Phillip I. Good
Common Errors in Statistics and How to Avoid Them Third Edition and Introduction to Statistics Through Resampling Methods and R S PLUS Set Book PDF

Author : Phillip I. Good
Publisher : Wiley
Page : 0 pages
File Size : 51,9 Mb
Release : 2009-07-07
Category : Mathematics
ISBN : 0470555793

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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 Pdf

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)

Tracking Environmental Change Using Lake Sediments

John B.H. Birks,André F. Lotter,Steve Juggins,John P. Smol
Tracking Environmental Change Using Lake Sediments Book PDF

Author : John B.H. Birks,André F. Lotter,Steve Juggins,John P. Smol
Publisher : Springer Science & Business Media
Page : 751 pages
File Size : 47,9 Mb
Release : 2012-04-08
Category : Science
ISBN : 9789400727441

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Tracking Environmental Change Using Lake Sediments by John B.H. Birks,André F. Lotter,Steve Juggins,John P. Smol Pdf

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

H. John B. Birks,André F. Lotter,Steve Juggins,John P. Smol
Tracking Environmental Change Using Lake Sediments Book PDF

Author : H. John B. Birks,André F. Lotter,Steve Juggins,John P. Smol
Publisher : Springer Science & Business Media
Page : 751 pages
File Size : 40,5 Mb
Release : 2012-04-06
Category : Science
ISBN : 9789400727458

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Tracking Environmental Change Using Lake Sediments by H. John B. Birks,André F. Lotter,Steve Juggins,John P. Smol Pdf

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.

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

Phillip I. Good,James W. Hardin
Common Errors in Statistics and How to Avoid Them 2nd Edition Introduction to Statistics Through Resampling Methods and Microsoft Office Excel Book PDF

Author : Phillip I. Good,James W. Hardin
Publisher : Wiley-Interscience
Page : 0 pages
File Size : 46,5 Mb
Release : 2008-03-14
Category : Mathematics
ISBN : 0470388102

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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,James W. Hardin Pdf

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.

Permutation Tests for Complex Data

Fortunato Pesarin,Luigi Salmaso
Permutation Tests for Complex Data Book PDF

Author : Fortunato Pesarin,Luigi Salmaso
Publisher : John Wiley & Sons
Page : 448 pages
File Size : 41,5 Mb
Release : 2010-02-25
Category : Mathematics
ISBN : 0470689528

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Permutation Tests for Complex Data by Fortunato Pesarin,Luigi Salmaso Pdf

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.

Mathematical Statistics with Resampling and R

Laura M. Chihara,Tim C. Hesterberg
Mathematical Statistics with Resampling and R Book PDF

Author : Laura M. Chihara,Tim C. Hesterberg
Publisher : John Wiley & Sons
Page : 432 pages
File Size : 47,9 Mb
Release : 2012-09-05
Category : Mathematics
ISBN : 9781118518953

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Mathematical Statistics with Resampling and R by Laura M. Chihara,Tim C. Hesterberg Pdf

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.

Nonparametric Statistical Tests

Markus Neuhauser
Nonparametric Statistical Tests Book PDF

Author : Markus Neuhauser
Publisher : CRC Press
Page : 248 pages
File Size : 49,6 Mb
Release : 2011-12-19
Category : Mathematics
ISBN : 9781439867044

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Nonparametric Statistical Tests by Markus Neuhauser Pdf

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. The author considers example data sets in each chapter to illustrate methods. Numerous real-life data from various areas, including the bible, and their analyses provide for greatly diversified reading. The book covers: Nonparametric two-sample tests for the location-shift model, specifically the Fisher-Pitman permutation test, the Wilcoxon rank sum test, and the Baumgartner-Weiss-Schindler test Permutation tests, location-scale tests, tests for the nonparametric Behrens-Fisher problem, and tests for a difference in variability Tests for the general alternative, including the (Kolmogorov-)Smirnov test, ordered categorical, and discrete numerical data Well-known one-sample tests such as the sign test and Wilcoxon’s signed rank test, a modification suggested by Pratt (1959), a permutation test with original observations, and a one-sample bootstrap test are presented. Tests for more than two groups, the following tests are described in detail: the Kruskal-Wallis test, the permutation F test, the Jonckheere-Terpstra trend test, tests for umbrella alternatives, and the Friedman and Page tests for multiple dependent groups The concepts of independence and correlation, and stratified tests such as the van Elteren test and combination tests The applicability of computer-intensive methods such as bootstrap and permutation tests for non-standard situations and complex designs Although the major development of nonparametric methods came to a certain end in the 1970s, their importance undoubtedly persists. What is still needed is a computer assisted evaluation of their main properties. This book closes that gap.

Probability and Statistical Inference

Robert Bartoszynski,Magdalena Niewiadomska-Bugaj
Probability and Statistical Inference Book PDF

Author : Robert Bartoszynski,Magdalena Niewiadomska-Bugaj
Publisher : John Wiley & Sons
Page : 592 pages
File Size : 40,7 Mb
Release : 2020-12-09
Category : Mathematics
ISBN : 9781119243823

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Probability and Statistical Inference by Robert Bartoszynski,Magdalena Niewiadomska-Bugaj Pdf

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.

Artificial Intelligence Methods in the Environmental Sciences

Sue Ellen Haupt,Antonello Pasini,Caren Marzban
Artificial Intelligence Methods in the Environmental Sciences Book PDF

Author : Sue Ellen Haupt,Antonello Pasini,Caren Marzban
Publisher : Springer Science & Business Media
Page : 418 pages
File Size : 40,9 Mb
Release : 2008-11-28
Category : Science
ISBN : 9781402091193

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Artificial Intelligence Methods in the Environmental Sciences by Sue Ellen Haupt,Antonello Pasini,Caren Marzban Pdf

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.

Resampling Methods

Phillip I. Good
Resampling Methods Book PDF

Author : Phillip I. Good
Publisher : Springer Science & Business Media
Page : 229 pages
File Size : 48,9 Mb
Release : 2006-12-31
Category : Mathematics
ISBN : 9780817644444

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Resampling Methods by Phillip I. Good Pdf

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.

Handbook of Educational Psychology

Patricia A. Alexander,PHILIP H WINNE
Handbook of Educational Psychology Book PDF

Author : Patricia A. Alexander,PHILIP H WINNE
Publisher : Routledge
Page : 2419 pages
File Size : 49,7 Mb
Release : 2012-11-12
Category : Education
ISBN : 9781135283513

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Handbook of Educational Psychology by Patricia A. Alexander,PHILIP H WINNE Pdf

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.

Comparing Groups

Andrew S. Zieffler,Jeffrey R. Harring,Jeffrey D. Long
Comparing Groups Book PDF

Author : Andrew S. Zieffler,Jeffrey R. Harring,Jeffrey D. Long
Publisher : John Wiley & Sons
Page : 332 pages
File Size : 45,8 Mb
Release : 2011-07-08
Category : Social Science
ISBN : 9781118063668

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Comparing Groups by Andrew S. Zieffler,Jeffrey R. Harring,Jeffrey D. Long Pdf

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.

Statistics for Linguistics with R

Stefan Th. Gries
Statistics for Linguistics with R Book PDF

Author : Stefan Th. Gries
Publisher : Walter de Gruyter
Page : 374 pages
File Size : 46,8 Mb
Release : 2013-03-22
Category : Language Arts & Disciplines
ISBN : 9783110307474

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Statistics for Linguistics with R by Stefan Th. Gries Pdf

This book is the revised and extended second edition of Statistics for Linguistics with R. The volume is an introduction to statistics for linguists using the open source software R. It is aimed at students and instructors/professors with little or no statistical background and is written in a non-technical and reader-friendly/accessible style. It first introduces in detail the overall logic underlying quantitative studies: exploration, hypothesis formulation and operationalization, and the notion and meaning of significance tests. It then introduces some basics of the software R relevant to statistical data analysis. A chapter on descriptive statistics explains how summary statistics for frequencies, averages, and correlations are generated with R and how they are graphically represented best. A chapter on analytical statistics explains how statistical tests are performed in R on the basis of many different linguistic case studies: For nearly every single example, it is explained what the structure of the test looks like, how hypotheses are formulated, explored, and tested for statistical significance, how the results are graphically represented, and how one would summarize them in a paper/article. A chapter on selected multifactorial methods introduces how more complex research designs can be studied: methods for the study of multifactorial frequency data, correlations, tests for means, and binary response data are discussed and exemplified step-by-step. Also, the exploratory approach of hierarchical cluster analysis is illustrated in detail. The book comes with many exercises, boxes with short think breaks and warnings, recommendations for further study, and answer keys as well as a statistics for linguists newsgroup on the companion website. Just like the first edition, it is aimed at students, faculty, and researchers with little or no statistical background in statistics or the open source programming language R. It avoids mathematical jargon and discusses the logic and structure of quantitative studies and introduces descriptive statistics as well as a range of monofactorial statistical tests for frequencies, distributions, means, dispersions, and correlations. The comprehensive revision includes new small sections on programming topics that facilitate statistical analysis, the addition of a variety of statistical functions readers can apply to their own data, a revision of overview sections on statistical tests and regression modeling, a complete rewrite of the chapter on multifactorial approaches, which now contains sections on linear regression, binary and ordinal logistic regression, multinomial and Poisson regression, and repeated-measures ANOVA, and a new visual tool to identify the right statistical test for a given problem and data set. The amount of code available from the companion website has doubled in size, providing much supplementary material on statistical tests and advanced plotting.