Introductory Statistics with R, Statistics and Computing
This is a nice book on statistical methods and statistical computing in R, a language and environment for statistical computing and graphs: this dialect of the S language is available as free software through internet. The fact that R is based on a formal computer language gives it tremendous flexibility, which is very useful for ad hoc model building in analysis of a complex data. The book is not a manual of R, but introduces a number of basic concepts and techniques that should allow the reader to get started with practical statistics.
The book covers the curriculum for a course in basic statistics. It presents one- and two-sample tests (t-tests with their distribution-free counterparts), linear models (ANOVA, simple and multiple linear regression), contingency tables, power calculations and computation of the sample size. It also presents some methods that are not typical for elementary statistical courses: logistic regression and survival analysis. The appendices describe how to obtain and install R, a systematic description of original data sets used in the book, and a compendium of R functions and commands. Explanation of statistical methods, together with an interpretation of statistical concepts, is the prevailing style of the text. They are illustrated by plenty of practical examples, all computed using R. This book will be useful for novices in applied statistics or in computing in R.