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

"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 Copyright