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Software Design, Testing and Engineering

R Cookbook (O'Reilly Cookbooks)

With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression.

Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process.

  • Create vectors, handle variables, and perform other basic functions
  • Input and output data
  • Tackle data structures such as matrices, lists, factors, and data frames
  • Work with probability, probability distributions, and random variables
  • Calculate statistics and confidence intervals, and perform statistical tests
  • Create a variety of graphic displays
  • Build statistical models with linear regressions and analysis of variance (ANOVA)
  • Explore advanced statistical techniques, such as finding clusters in your data

"Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time." —Jeffrey Ryan, software consultant and R package author




The Art of R Programming: A Tour of Statistical Software Design

R in a Nutshell: A Desktop Quick Reference

Doing Bayesian Data Analysis: A Tutorial with R and BUGS

Data Analysis with Open Source Tools

Data Mining with R: Learning with Case Studies (Chapman & Hall/CRC Data Mining and Knowledge Discove
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