R is an Open Source implementation of the well-known S language. It works on multiple computing platforms and can be freely downloaded. R is thus ideally suited 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.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
1 Basics 1
2 The R environment 31
3 Probability and distributions 55
4 Descriptive statistics and graphics 67
5 One- and two-sample tests 95
6 Regression and correlation 109
7 Analysis of variance and the Kruskal-Wallis test 127
8 Tabular data 145
9 Power and the computation of sample size 155
10 Advanced data handling 163
11 Multiple regression 185
12 Linear models 195
13 Logistic regression 227
14 Survival analysis 249
15 Rates and Poisson regression 259
16 Nonlinear curve fitting 275
A Obtaining and installing R and the ISwR package 289
B Data sets in the ISwR package 293
C Compendium 325
D Answers to exercises 337
Bibliography 355
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