Road map for self-study before the training school

We will be using basically two programs: R and RStudio. However, we will use R from within RStudio. R can be extended by means of packages, which can be downloadedand installed directly from within RStudio.

The road map below should help you find your way through the very many sources of information available on line. I have tried to suggest a sequence of reading/watching/practice that will prepare you follow the contents to be presented during the training school.

Start as soon as possible, as there is quite a lot of material here. Depending on your previous experience going through these may take a rather long time.

1. Get to know R, Why use the R language? (@ Burns Statistics), and a little bit of its history and some examples (@ Wikipedia).

2. A short Intro to R (@ Princeton) or a longer and more entertaining Impatient R (@ Burns Statistics)

3. Give R a try. Play with R in your browser (preferably Chrome) at the R-Fiddle site.

4. Intro to RStudio

5. Install R and RStudio on your computer

5. Intro to R video series

6. ggplot2 and grammar of graphics

7. Excel and its problems (spreadsheet addition) You should take this linked text with a pinch of salt, as some of the examples are quite old. Pedro’s opinion: it is not worthwhile spending time working on your data in Excel. Try to do everything in R, or (if really needed) use grep, awk, Perl, Phyton, etc. to sort the data. Matt opinion: Excel is good for data entry and checking. We both agree that statistical analyses should, unless extremely simple, be done with statistical software such as R rather than in a spreadsheet.


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