Introductory Statistics with R

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Springer Science & Business Media, Aug 15, 2008 - Computers - 363 pages
12 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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Review: Introductory Statistics with R (Statistics and Computing)

User Review  - Goodreads

Though the book is very informative, I still found it to be at a difficulty level not suitable to the beginner. R is quite complicated anyway. The instructions to make use of it need to be put as simply as possible. Nonetheless, the book is well organized, and detailed. A good textbook. Read full review

Review: Introductory Statistics with R (Statistics and Computing)

User Review  - Jyotika Varmani - Goodreads

Though the book is very informative, I still found it to be at a difficulty level not suitable to the beginner. R is quite complicated anyway. The instructions to make use of it need to be put as simply as possible. Nonetheless, the book is well organized, and detailed. A good textbook. Read full review

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