# Beginning R: An Introduction to Statistical Programming

Apress, Nov 28, 2012 - Computers - 336 pages
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

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### Contents

 CHAPTER 1 Getting R and Getting Started 1 CHAPTER 2 Programming in R 25 CHAPTER 3 Writing Reusable Functions 47 CHAPTER 4 Summary Statistics 65 CHAPTER 5 Creating Tables and Graphs 77 CHAPTER 6 Discrete Probability Distributions 93 CHAPTER 7 Computing Normal Probabilities 103 CHAPTER 8 Creating Confidence Intervals 113
 CHAPTER 12 Correlation and Regression 165 CHAPTER 13 Multiple Regression 185 CHAPTER 14 Logistic Regression 201 CHAPTER 15 ChiSquare Tests 217 CHAPTER 16 Nonparametric Tests 229 CHAPTER 17 Using R for Simulation 247 Resampling and Bootstrapping 257 CHAPTER 19 Making an R Package 269

 CHAPTER 9 Performing t Tests 125 CHAPTER 10 OneWay Analysis of Variance 139 CHAPTER 11 Advanced Analysis of Variance 149
 CHAPTER 20 The R Commander Package 289 Index 303 Copyright