Learning R

Appendix E. Bibliography

1. Jason R. Briggs. Python for Kids: A Playful Introduction to Programming. 2012. William Pollock. ISBN-13 978-1-59327-407-8.
2. Garrett Grolemund. Data Analysis with R. 2013. O’Reilly. ISBN-13 978-1-4493-5901-0.
3. Andrie de Vries and Joris Meys. R For Dummies. 2012. John Wiley & Sons. ISBN-13 978-1-1199-6284-7.
4. Michael Fitzgerald. Introducing Regular Expressions. 2012. O’Reilly. ISBN-13 978-1-4493-9268-0.
5. Paul Murrell. R Graphics, Second Edition. 2011. Chapman and Hall/CRC. ISBN-13 978-1-4398-3176-2.
6. Hadley Wickham. ggplot2: Elegant Graphics for Data Analysis. 2010. Springer. ISBN-13 978-0-3879-8140-6.
7. Deepayan Sarkar. Lattice: Multivariate Data Visualization with R. 2008. Springer. ISBN-13 978-0-3877-5968-5.
8. Edward R. Tufte. Envisioning Information. 1990. Graphics Press USA. ISBN-13 978-0-9613-9211-6.
9. Michael J. Crawley. The R Book. 2013. John Wiley & Sons. ISBN-13 978-0-4709-7392-9.
10. Andy Field, Jeremy Miles, and Zoe Field. Discovering Statistics Using R. 2012. SAGE Publications. ISBN-13 978-1-4462-0046-9.
11. Max Kuhn. Applied Predictive Modeling. 2013. Springer. ISBN-13 978-1-4614-6848-6.
12. John Fox and Sanford Weisberg. An R Companion to Applied Regression. 2011. SAGE Publications. ISBN-13 978-1-4129-7514-8.
13. José Pinheiro and Douglas Bates. Mixed-Effects Models in S and S-PLUS. 2009. Springer. ISBN-13 978-1-4419-0317-4.
14. Graham Williams. Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery. 2011. Springer. ISBN-13 ...