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Statistics and Computing Ser.: Introductory Statistics with R by Peter Dalgaard (2008, Trade Paperback)

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About this product

Product Identifiers

PublisherSpringer New York

ISBN-100387790535

ISBN-139780387790534

eBay Product ID (ePID)66588261

Product Key Features

Number of PagesXvi, 364 Pages

Publication NameIntroductory Statistics with R

LanguageEnglish

Publication Year2008

SubjectProgramming Languages / General, Mathematical & Statistical Software, Probability & Statistics / General, Bioinformatics

TypeTextbook

Subject AreaMathematics, Computers

AuthorPeter Dalgaard

SeriesStatistics and Computing Ser.

FormatTrade Paperback

Dimensions

Item Weight42 Oz

Item Length9.3 in

Item Width6.1 in

Additional Product Features

Edition Number2

Intended AudienceScholarly & Professional

Dewey Edition21

Number of Volumes1 vol.

IllustratedYes

Dewey Decimal519.5

Table Of ContentBasics.- The R environment.- Probability and distributions.- Descriptive statistics and graphics.- One- and two-sample tests.- Regression and correlation.- Analysis of variance and the Kruskal-Wallis test.- Tabular data.- Power and the computation of sample size.- Advanced data handling.- Multiple regression.- Linear models.- Logistic regression.- Survival analysis.- Rates and Poisson regression.- Nonlinear curve fitting.

SynopsisR is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. R is now in widespread use for teaching at many levels as well as for practical data analysis and methodological development. This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. A supplementary R package can be downloaded and contains the data sets. The statistical methodology includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one- and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last six chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, survival analysis, Poisson regression, and nonlinear regression. In the second edition, the text and code have been updated to R version 2.6.2. The last two methodological chapters are new, as is a chapter on advanced data handling. The introductory chapter has been extended and reorganized as two chapters. Exercises have been revised and answers are now provided in an Appendix., This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. This new edition has been updated to R 2.6.2 and features new and expanded coverage., This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one- and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.

LC Classification NumberQA273.A1-274.9