A Handbook Of Statistical Analyses Using R Second Edition

Download or read book A Handbook of Statistical Analyses Using R, Second Edition written by Torsten Hothorn and published by Chapman and Hall/CRC. This book was released on 2009-07-20 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book A Handbook of Statistical Analyses using R, Third Edition written by Torsten Hothorn and published by CRC Press. This book was released on 2014-06-25 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Handbook of Statistical Analyses Using Stata written by Brian S. Everitt and published by CRC Press. This book was released on 2006-11-15 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, AHandbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many

Download or read book A Handbook of Statistical Analyses Using S-PLUS written by Brian S. Everitt and published by CRC Press. This book was released on 2019-05-07 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the first edition of this book was published, S-PLUS has evolved markedly with new methods of analysis, new graphical procedures, and a convenient graphical user interface (GUI). Today, S-PLUS is the statistical software of choice for many applied researchers in disciplines ranging from finance to medicine. Combining the command line languag

Download or read book Handbook of Statistical Analysis and Data Mining Applications written by Ken Yale and published by Elsevier. This book was released on 2017-11-09 with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Download or read book The R Book written by Michael J. Crawley and published by John Wiley & Sons. This book was released on 2007-06-13 with total page 953 pages. Available in PDF, EPUB and Kindle. Book excerpt: The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.

Download or read book R for Statistics written by Pierre-Andre Cornillon and published by CRC Press. This book was released on 2012-03-21 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although there are currently a wide variety of software packages suitable for the modern statistician, R has the triple advantage of being comprehensive, widespread, and free. Published in 2008, the second edition of Statistiques avec R enjoyed great success as an R guidebook in the French-speaking world. Translated and updated, R for Statistics includes a number of expanded and additional worked examples. Organized into two sections, the book focuses first on the R software, then on the implementation of traditional statistical methods with R. Focusing on the R software, the first section covers: Basic elements of the R software and data processing Clear, concise visualization of results, using simple and complex graphs Programming basics: pre-defined and user-created functions The second section of the book presents R methods for a wide range of traditional statistical data processing techniques, including: Regression methods Analyses of variance and covariance Classification methods Exploratory multivariate analysis Clustering methods Hypothesis tests After a short presentation of the method, the book explicitly details the R command lines and gives commented results. Accessible to novices and experts alike, R for Statistics is a clear and enjoyable resource for any scientist. Datasets and all the results described in this book are available on the book’s webpage at http://www.agrocampus-ouest.fr/math/RforStat