Introductory Statistics with R

by Peter Dalgaard

Springer. ISBN 0-387-95475-9, 2002.

Paperback 229mm 155mm, xv+267 pages

[Image of Cover]

Published in August 2002.


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
  2. Probability and Distributions
  3. Descriptive Statistics and Graphics
  4. One and two-sample tests
  5. Regression and Correlation
  6. ANOVA and Kruskal-Wallis
  7. Tabular Data
  8. Power and the Computation of Sample Size
  9. Multiple Regression
  10. Linear Models
  11. Logistic Regression
  12. Survival Analysis


  1. Obtaining and Installing R
  2. Data Sets in the ISwR Package
  3. Compendium

Errata and Notes

(Most of these were fixed in the corrected 3rd printing.)

Answers to Exercises

A preliminary set of short answers can be found at
Last edited on July 3, 2006 by Peter Dalgaard