R for Everyone : Advanced Analytics and Graphics

Using the free, open source R language, scientists, financial analysts, public policy professionals, and programmers can build powerful statistical models capable of answering many of their most challenging questions. But, for non-statisticians, R can be difficult to learn—and most books on the subject assume far too much knowledge to help the non-statistician. R for Everyone is the solution. Drawing on his extensive experience teaching new users through the New York City R User Group, professional statistician Jared Lander has written the perfect R tutorial for everyone who's new to statistical programming and modeling.

SalientFeatures

• Based on a course on R and Big Data taught by the author atColumbia
• Designed from the ground up to help readers quickly overcome R'slearning curve
• Packed with hands-on practice opportunities and realistic, downloadablecode examples
• By an author with unsurpassed experience teaching statisticalprogramming and modeling to novices
• For every potential R user: programmers, data scientists, DBAs, marketers,quants, scientists, policymakers, and many others

Table Of Content

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

Appendix B: Glossary