Beginning R : the statistical programming language / Mark Gardener.

Includes index.

1. Introducing R: what it is and how to get it -- 2. Starting out: becoming familiar with R -- 3. Starting out: working with objects -- 4. Data: descriptive statistics and tabulation -- 5. Data: distribution -- 6. Simple hypothesis testing -- 7. Introduction to graphical analysis -- 8. Formula notation and complex statistics -- 9. Manipulating data and extracting components -- 10. Regression (linear modeling) -- 11. More about graphs -- 12. Writing your own scripts: beginning to program.

Conquer the complexities of this open source statistical language R is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a user friendly context. Both students and workers in fields that require extensive statistical analysis will find this book helpful as they learn to use R for simple summary statistics, hypothesis testing, creating graphs, regression, and much more. It covers formula notation, complex statistics, manipulating data and extracting components, and rudimentary programming R, the open source statistical language increasingly used to handle statistics and produces publication quality graphs, is notoriously complex. This book makes R easier to understand through the use of simple statistical examples, teaching the necessary elements in the context in which R is actually used Covers getting started with R and using it for simple summary statistics, hypothesis testing, and graphs. Shows how to use R for formula notation, complex statistics, manipulating data, extracting components, and regression. Provides beginning programming instruction for those who want to write their own scripts Beginning R offers anyone who needs to perform statistical analysis the information necessary to use R with confidence.