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Introductory Statistics With R (2ND 08 Edition)

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Introductory Statistics With R (2ND 08 Edition) Cover

 

Synopses & Reviews

Publisher Comments:

R 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. Peter Dalgaard is associate professor at the Department of Biostatistics at the University of Copenhagen and has extensive experience in teaching within the PhD curriculum at the Faculty of Health Sciences. He has been a member of the R Core Team since 1997.

Synopsis:

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.

Synopsis:

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.

About the Author

Peter Dalgaard is associate professor at the Biostatistical Department at the University of Copenhagen and has extensive experience in teaching within the PhD curriculum at the Faculty of Health Sciences. He was chairman of the Danish Society for Theoretical Statistics from 1996 to 2000. Peter Dalgaard has been a key member of the R Core Team since August 1997 and is well known among R users for his activity on

Table of Contents

Basics. - The R environment. - Probability and statistics. - Descriptive statistics and graphics. - One and two sample tests. - Regression and correlation. - ANOVA and Kruskal-Wallis. - 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. - Obtaining and installing R and the ISwR package. - Data sets in the ISwR package. - Compendium. - Answers to exercises. - Index.

Product Details

ISBN:
9780387790534
Author:
Dalgaard, Peter
Publisher:
Springer
Subject:
Probability & Statistics - General
Subject:
Bioinformatics
Subject:
Statistics
Subject:
Data processing
Subject:
Statistics -- Data processing.
Subject:
R (Computer program language)
Subject:
Mathematical & Statistical Software
Subject:
Mathematics | Probability and Statistics
Subject:
Statistics and Computing/Statistics Programs
Subject:
Computer Appl. in Life Sciences
Copyright:
Edition Description:
2nd ed. 2008
Series:
Statistics and Computing
Publication Date:
20080815
Binding:
TRADE PAPER
Language:
English
Illustrations:
Y
Pages:
380
Dimensions:
235 x 155 mm 1190 gr

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Introductory Statistics With R (2ND 08 Edition) New Trade Paper
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$59.75 In Stock
Product details 380 pages Springer - English 9780387790534 Reviews:
"Synopsis" by , 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.
"Synopsis" by , 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.
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