Beginning R: The Statistical Programming Language Front Cover

Beginning R: The Statistical Programming Language

  • Length: 504 pages
  • Edition: 1
  • Publisher:
  • Publication Date: 2012-06-05
  • ISBN-10: 111816430X
  • ISBN-13: 9781118164303
  • Sales Rank: #833849 (See Top 100 Books)
Description

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.

Table of Contents

Chapter 1: Introducing R: What It Is and How to Get It
Chapter 2: Starting Out: Becoming Familiar with R
Chapter 3: Starting Out: Working
Chapter 4: Data: Descriptive Statistics and Tabulation
Chapter 5: Data: Distribution
Chapter 6: Simple Hypothesis Testing
Chapter 7: Introduction to Graphical Analysis
Chapter 8: Formula Notation and Complex Statistics
Chapter 9: Manipulating Data and Extracting Components
Chapter 10: Regression (Linear Modeling)
Chapter 11: More About Graphs
Chapter 12: Writing Your Own Scripts: Beginning to Program
Appendix: Answers to Exercises

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