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. Beginning R offers anyone who needs to perform statistical analysis the information necessary to use R with confidence. Learning the R Language 1. Getting R and Getting Started 2.
Programming in R 3. Writing Reusable Functions 4. Summary Statistics Part II. Using R for Descriptive Statistics 5. Creating Tables and Graphs 6. Discrete Probability Distributions 7. Using R for Inferential Statistics 8. Creating Confidence Intervals 9. Performing t Tests Simple Correlation and Regression in R Multiple Correlation and Regression in R It's not very long, yet is a good introduction for R.
It also touches on programming. R Tips by Paul E. Johnson - Another excellent book introducing the major concepts of working with R. The content is very similar to R for Beginners , but the presentation is a little different. Strongly recommended. The physical book is available for purchase, or you can download a copy of it for free.
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