Learning R

Preface

R is a programming language and a software environment for data analysis and statistics. It is a GNU project, which means that it is free, open source software. It is growing exponentially by most measures—most estimates count over a million users, and it has over 4,000 add-on packages contributed by the community, with that number increasing by about 25% each year. The Tiobe Programming Community Index of language popularity places it at number 24 at the time of this writing, roughly on a par with SAS and MATLAB.

R is used in almost every area where statistics or data analyses are needed. Finance, marketing, pharmaceuticals, genomics, epidemiology, social sciences, and teaching are all covered, as well as dozens of other smaller domains.

About This Book

Since R is primarily designed to let you do statistical analyses, many of the books written about R focus on teaching you how to calculate statistics or model datasets. This unfortunately misses a large part of the reality of analyzing data. Unless you are doing cutting-edge research, the statistical techniques that you use will often be routine, and the modeling part of your task may not be the largest one. The complete workflow for analyzing data looks more like this:

1. Retrieve some data.
2. Clean the data.
3. Explore and visualize the data.
4. Model the data and make predictions.
5. Present or publish your results.

Of course at each stage your results may generate interesting questions that lead you to look for more data, or for ...