R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics

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"O'Reilly Media, Inc.", Mar 3, 2011 - Computers - 438 pages

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

 

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User Review  - nmarun - LibraryThing

I agree that this is not a book for the beginners, but nevertheless it started with the very basics. I was impressed about it though it is from a Cookbook series. The approach in the book is: if this ... Read full review

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Contents

Chapter 1 Getting Started and Getting Help
1
Chapter 2 Some Basics
23
Chapter 3 Navigating the Software
51
Chapter 4 Input and Output
71
Chapter 5 Data Structures
95
Chapter 6 Data Transformations
147
Chapter 7 Strings and Dates
161
Chapter 8 Probability
177
Chapter 9 General Statistics
195
Chapter 10 Graphics
221
Chapter 11 Linear Regression and ANOVA
267
Chapter 12 Useful Tricks
313
Chapter 13 Beyond Basic Numerics and Statistics
335
Chapter 14 Time Series Analysis
355
Index
397
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