# Beginning R

*Beginning R: An Introduction to Statistical Programming* is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics.

R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research.

- Covers the freely-available R language for statistics
- Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more
- Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done

**What you’ll learn**

- Acquire and install R
- Import and export data and scripts
- Generate basic statistics and graphics
- Program in R to write custom functions
- Use R for interactive statistical explorations
- Implement simulations and other advanced techniques

**Who this book is for**

*Beginning R: An Introduction to Statistical Programming* is an easy-to-read book that serves as an instruction manual and reference for working professionals, professors, and students who want to learn and use R for basic statistics. It is the perfect book for anyone needing a free, capable, and powerful tool for exploring statistics and automating their use.

**Table of Contents**

Part I: Learning the R Language

Chapter 1. Getting R and Getting Started

Chapter 2. Programming in R

Chapter 3. Writing Reusable Functions

Chapter 4. Summary Statistics

Part II: Using R for Descriptive Statistics

Chapter 5. Creating Tables and Graphs

Chapter 6. Discrete Probability Distributions

Chapter 7. Computing Standard Normal Probabilities

Part III: Using R for Inferential Statistics

Chapter 8. Creating Confidence Intervals

Chapter 9. Performing t Tests

Chapter 10. Implementing One-Way ANOVA

Chapter 11. Implementing Advanced ANOVA

Chapter 12. Simple Correlation and Regression in R

Chapter 13. Multiple Correlation and Regression in R

Chapter 14. Logistic Regression

Chapter 15. Performing Chi-Square Tests

Chapter 16. Working in Nonparametric Statistics

Part IV: Taking R to the Next Level

Chapter 17. Using R for Simulation

Chapter 18. Resampling and Bootstrapping

Chapter 19. Creating R Packages

Chapter 20. Executing R Packages

### Book Details

**Paperback:**336 pages**Publisher:**Apress (October 2012)**Language:**English**ISBN-10:**1430245549**ISBN-13:**978-1430245544