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

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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

About the Author
Paul Teetor
is a quantitative developer with Masters degrees in statistics and computer science. He specializes in analytics and software engineering for investment management, securities trading, and risk management. He works with hedge funds, market makers, and portfolio managers in the greater Chicago area.

Table of Contents

Chapter 1 Getting Started and Getting Help

Chapter 2 Some Basics

Chapter 3 Navigating the Software

Chapter 4 Input and Output

Chapter 5 Data Structures

Chapter 6 Data Transformations

Chapter 7 Strings and Dates

Chapter 8 Probability

Chapter 9 General Statistics

Chapter 10 Graphics

Chapter 11 Linear Regression and ANOVA

Chapter 12 Useful Tricks

Chapter 13 Beyond Basic Numerics and Statistics

Chapter 14 Time Series Analysis



Paul Teetor
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Dimensions (W x H x D):
23 x 18 x 2.5 cms