Beginning R: The Statistical Programming Language

  • 8h 31m
  • Mark Gardener
  • John Wiley & Sons (US)
  • 2012

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.

About the Author

Dr. Mark Gardener is an ecologist, lecturer, and writer working in the UK. He is currently self-employed and runs courses in ecology, data analysis, and R for a variety of organizations.

In this Book

  • Introduction
  • Introducing R: What It Is and How to Get It
  • Starting Out: Becoming Familiar with R
  • Starting Out: Working With Objects
  • Data: Descriptive Statistics and Tabulation
  • Data: Distribution
  • Simple Hypothesis Testing
  • Introduction to Graphical Analysis
  • Formula Notation and Complex Statistics
  • Manipulating Data and Extracting Components
  • Regression (Linear Modeling)
  • More About Graphs
  • Writing Your Own Scripts: Beginning to Program
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