## Beginning R: An Introduction to Statistical Programming 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. 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 ContentsPart I. Learning the R Language1. 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. Computing Standard Normal Probabilities Part III. Using R for Inferential Statistics 8. Creating Confidence Intervals 9. Performing t Tests 10. Implementing One-Way ANOVA 11. Implementing Advanced ANOVA 12. Simple Correlation and Regression in R 13. Multiple Correlation and Regression in R 14. Logistic Regression 15. Performing Chi-Square Tests 16. Working in Nonparametric Statistics Part IV. Taking R to the Next Level 17. Using R for Simulation 18. Resampling and Bootstrapping 19. Creating R Packages 20. Executing R Packages |

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### Contents

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 14 Logistic Regression | 201 |

Chapter 15 ChiSquare Tests | 217 |

Chapter 16 Nonparametric Tests | 229 |

Chapter 17 Using R for Simulation | 247 |

Chapter 18 The New Statistics Resampling and Bootstrapping | 257 |

Chapter 19 Making an R Package | 269 |

Chapter 20 The R Commander Package | 289 |

303 | |

Chapter 9 Performing t Tests | 125 |

Chapter 10 OneWay Analysis of Variance | 139 |

Chapter 11 Advanced Analysis of Variance | 149 |

Chapter 12 Correlation and Regression | 165 |

Chapter 13 Multiple Regression | 185 |

vii | |

About the Author | xvii |

About the Technical Reviewer | xviii |

Acknowledgments | xix |