Introductory Statistics with R

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Springer Science & Business Media, Aug 15, 2008 - Computers - 363 pages
6 Reviews

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.

  

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LibraryThing Review

User Review  - pmorrison - LibraryThing

I found this a helpful guide in using R to analyze and present data for a paper I was writing. I stopped reading when the paper was submitted, and I don't have anything else to compare it against, but if you need to use R to some end, I'd recommend it. Read full review

User Review - Flag as inappropriate

This is a very good book to learn R with hands on exercises. The data sets that are used in the book are available and it is possible to cross check your doings.

Contents

2 The R environment
30
3 Probability and distributions
55
4 Descriptive statistics and graphics
66
5 Oneand twosample tests
95
6 Regression and correlation
109
7 Analysis of variance and the KruskalWallis test
126
8 Tabular data
145
9 Power and the computation of sample size
155
13 Logistic regression
226
14 Survival analysis
249
15 Rates and Poisson regression
259
16 Nonlinear curve fitting
275
A Obtaining and installing
289
B Data sets in the ISwR package1
293
C Compendium
324
D Answers to exercises
337

10 Advanced data handling
163
11 Multiple regression
185
12 Linear models
195

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About the author (2008)

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