Torsten Hothorn's Books

A Handbook of Statistical Analyses Using R, Second Edition

By: Torsten Hothorn,Brian S. Everitt

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A Handbook of Statistical Analyses Using R, Second Edition

By: Torsten Hothorn,Brian S. Everitt

A Proven Guide for Easily Using R to Effectively Analyze Data Like its bestselling predecessor, A Handbook of Statistical Analyses Using R, Second Edition provides a guide to data analysis using the R system for statistical computing. Each chapter includes a brief account of the relevant statistical background, along with appropriate references. New to the Second Edition New chapters on graphical displays, generalized additive models, and simultaneous inference A new section on generalized linear mixed models that completes the discussion on the analysis of longitudinal data where the response variable does not have a normal distribution New examples and additional exercises in several chapters A new version of the HSAUR package (HSAUR2), which is available from CRAN This edition continues to offer straightforward descriptions of how to conduct a range of statistical analyses using R, from simple inference to recursive partitioning to cluster analysis. Focusing on how to use R and interpret the results, it provides students and researchers in many disciplines with a self-contained means of using R to analyze their data.

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383

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CRC Press

Published Date

ISBN 10

1420079336

ISBN 13

9781420079333

A Handbook of Statistical Analyses using R, Third Edition

By: Torsten Hothorn,Brian S. Everitt

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A Handbook of Statistical Analyses using R, Third Edition

By: Torsten Hothorn,Brian S. Everitt

Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis. New to the Third Edition Three new chapters on quantile regression, missing values, and Bayesian inference Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables Additional exercises More detailed explanations of R code New section in each chapter summarizing the results of the analyses Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses Whether you’re a data analyst, scientist, or student, this handbook shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results.

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454

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CRC Press

Published Date

ISBN 10

1482204584

ISBN 13

9781482204582

A Handbook of Statistical Analyses Using R

By: Torsten Hothorn,Brian S. Everitt

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A Handbook of Statistical Analyses Using R

By: Torsten Hothorn,Brian S. Everitt

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298

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CRC Press

Published Date

ISBN 10

1420010654

ISBN 13

9781420010657

An Introduction to Applied Multivariate Analysis with R

By: Brian Everitt,Torsten Hothorn

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An Introduction to Applied Multivariate Analysis with R

By: Brian Everitt,Torsten Hothorn

The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.

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Page Count

284

Publisher

Springer Science & Business Media

Published Date

ISBN 10

1441996508

ISBN 13

9781441996503

Multiple Comparisons Using R

By: Frank Bretz,Torsten Hothorn,Peter Westfall

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Multiple Comparisons Using R

By: Frank Bretz,Torsten Hothorn,Peter Westfall

Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples. It also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-project.org After giving examples of multiplicity problems, the book covers general concepts and basic multiple comparisons procedures, including the Bonferroni method and Simes’ test. It then shows how to perform parametric multiple comparisons in standard linear models and general parametric models. It also introduces the multcomp package in R, which offers a convenient interface to perform multiple comparisons in a general context. Following this theoretical framework, the book explores applications involving the Dunnett test, Tukey’s all pairwise comparisons, and general multiple contrast tests for standard regression models, mixed-effects models, and parametric survival models. The last chapter reviews other multiple comparison procedures, such as resampling-based procedures, methods for group sequential or adaptive designs, and the combination of multiple comparison procedures with modeling techniques. Controlling multiplicity in experiments ensures better decision making and safeguards against false claims. A self-contained introduction to multiple comparison procedures, this book offers strategies for constructing the procedures and illustrates the framework for multiple hypotheses testing in general parametric models. It is suitable for readers with R experience but limited knowledge of multiple comparison procedures and vice versa. See Dr. Bretz discuss the book.

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202

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CRC Press

Published Date

ISBN 10

1420010905

ISBN 13

9781420010909

A Handbook of Statistical Analyses using R, Third Edition

By: Torsten Hothorn,Brian S. Everitt

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A Handbook of Statistical Analyses using R, Third Edition

By: Torsten Hothorn,Brian S. Everitt

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454

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CRC Press

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ISBN 10

1482204584

ISBN 13

9781482204582

A Handbook of Statistical Analyses Using R, Second Edition

By: Torsten Hothorn,Brian S. Everitt

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A Handbook of Statistical Analyses Using R, Second Edition

By: Torsten Hothorn,Brian S. Everitt

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376

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Chapman and Hall/CRC

Published Date

ISBN 10

1420079336

ISBN 13

9781420079333

A Handbook of Statistical Analyses Using R

By: Torsten Hothorn,Brian S. Everitt

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A Handbook of Statistical Analyses Using R

By: Torsten Hothorn,Brian S. Everitt

R is dynamic, to say the least. More precisely, it is organic, with new functionality and add-on packages appearing constantly. And because of its open-source nature and free availability, R is quickly becoming the software of choice for statistical analysis in a variety of fields. Doing for R what Everitt's other Handbooks have done for S-PLUS, STATA, SPSS, and SAS, A Handbook of Statistical Analyses Using R presents straightforward, self-contained descriptions of how to perform a variety of statistical analyses in the R environment. From simple inference to recursive partitioning and cluster analysis, eminent experts Everitt and Hothorn lead you methodically through the steps, commands, and interpretation of the results, addressing theory and statistical background only when useful or necessary. They begin with an introduction to R, discussing the syntax, general operators, and basic data manipulation while summarizing the most important features. Numerous figures highlight R's strong graphical capabilities and exercises at the end of each chapter reinforce the techniques and concepts presented. All data sets and code used in the book are available as a downloadable package from CRAN, the R online archive. A Handbook of Statistical Analyses Using R is the perfect guide for newcomers as well as seasoned users of R who want concrete, step-by-step guidance on how to use the software easily and effectively for nearly any statistical analysis.

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304

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Chapman and Hall/CRC

Published Date

ISBN 10

1584885394

ISBN 13

9781584885399

Multiple Comparisons Using R

By: Frank Bretz,Torsten Hothorn,Peter Westfall

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Multiple Comparisons Using R

By: Frank Bretz,Torsten Hothorn,Peter Westfall

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Solve jigsaw puzzle

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Page Count

202

Publisher

CRC Press

Published Date

ISBN 10

1420010905

ISBN 13

9781420010909

Book's by Torsten Hothorn

A Handbook of Statistical Analyses Using R, Second Edition

A Handbook of Statistical Analyses Using R, Second Edition

A Handbook of Statistical Analyses using R, Third Edition

A Handbook of Statistical Analyses using R, Third Edition

A Handbook of Statistical Analyses Using R

A Handbook of Statistical Analyses Using R

An Introduction to Applied Multivariate Analysis with R

An Introduction to Applied Multivariate Analysis with R

Multiple Comparisons Using R

Multiple Comparisons Using R

A Handbook of Statistical Analyses using R, Third Edition

A Handbook of Statistical Analyses using R, Third Edition

A Handbook of Statistical Analyses Using R, Second Edition

A Handbook of Statistical Analyses Using R, Second Edition

A Handbook of Statistical Analyses Using R

A Handbook of Statistical Analyses Using R

Multiple Comparisons Using R

Multiple Comparisons Using R

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