R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics 2nd Edition
by JD Long (Author), Paul Teetor (Author)

About the Author
J.D. Long is a misplaced southern agricultural econo-mist currently working for Renaissance Re in New York City. J.D. is an avid user of Python, R, AWS and colorful metaphors, and is a frequent presenter at R conferences as well as the founder of the Chicago R User Group. He lives in Jersey City, NJ with his wife, a recovering trial lawyer, and his 11-year-old circuit bending daughter.
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.

About this book
With more than 275 practical recipes, this expanded edition 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. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression.
Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an intermediate user, this book 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
• Simplify data input and output
• 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
  

Brief contents
1. Getting Started and Getting Help
2. Some Basics
3. Navigating the Software
4. Input and Output
5. Data Structures
6. Data Transformations
7. Strings and Dates
8. Probability
9. General Statistics
10. Graphics
11. Linear Regression and ANOVA
12. Useful Tricks
13. Beyond Basic Numerics and Statistics
14. Time Series Analysis
15. Simple Programming
16. R Markdown and Publishing
Index

Pages: 500 pages
Publisher: O'Reilly Media; 2 edition (July 26, 2019)
Language: English
ISBN-10: 1492040681
ISBN-13: 978-1492040682