Warning

Here are the notes I took while discovering and using the statistical environment R. However, I do not claim any competence in the domains I tackle: I hope you will find those notes useful, but keep you eyes open -- errors and bad advice are still lurking in those pages...

Should you want it, I have prepared a quick-and-dirty PDF version of this document.

The old, French version is still available, in HTML or as a single file.

You may also want all the code in this document.

1. Introduction to R

2. Programming in R

3. From Data to Graphics

4. Customizing graphics

5. Factorial methods: Around Principal Component Analysis (PCA)

6. Clustering

7. Probability Distributions

8. Estimators and Statistical Tests

9. Regression

10. Other regressions

11. Regression Problems -- and their Solutions

12. Generalized Linear Models: logistic regression, Poisson regression, etc.

13. Analysis of Variance (Anova)

14. Mixed Models

15. Time series

16. Miscellaneous

17. Applications





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