R for Everyone: Advanced Analytics and Graphics, 2nd edition

Published by Addison-Wesley Professional (June 13, 2017) © 2017

  • Jared P. Lander
Products list
  • Available for purchase from all major ebook resellers, including InformIT.com
Products list

Details

  • A print text
  • Free shipping
  • Also available for purchase as an ebook from all major ebook resellers, including InformIT.com

This product is expected to ship within 3-6 business days for US and 5-10 business days for Canadian customers.

Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone, Second Edition, is the solution.

Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks.

Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques.

By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most.

  • Chapter 1: Getting R 11.1 Downloading R
  • Chapter 2: The R Environment
  • Chapter 3: R Packages
  • Chapter 4: Basics of R
  • Chapter 5: Advanced Data Structures
  • Chapter 6: Reading Data into R
  • Chapter 7: Statistical Graphics
  • Chapter 8: Writing R Functions
  • Chapter 9: Control Statements
  • Chapter 10: Loops, the Un-R Way to Iterate
  • Chapter 11: Group Manipulation
  • Chapter 12: Data Reshaping
  • Chapter 13: Manipulating Strings
  • Chapter 14: Probability Distributions
  • Chapter 15: Basic Statistics
  • Chapter 16: Linear Models
  • Chapter 17: Generalized Linear Models
  • Chapter 18: Model Diagnostics
  • Chapter 19: Regularization and Shrinkage
  • Chapter 20: Nonlinear Models
  • Chapter 21: Time Series and Autocorrelation
  • Chapter 22: Clustering
  • Chapter 23: Reproducibility, Reports and Slide Shows with knitr
  • Chapter 24: Building R Packages
  • Appendix A: Real-Life Resources 
  • A.1 Meetups
  • A.2 Stackoverflow
  • A.3 Twitter
  • A.4 Conferences
  • A.5 Web Sites
  • A.6 Documents
  • A.7 Books
  • A.8 Conclusion
  • Appendix B: Glossary

Need help? Get in touch