R-bloggers

2012-08-23

Learn the R language for Statistical Computing and Graphics

I hope this post is the beginning to a series on how to get up to speed using R. R is GNU S. If the previous sentence seems alien to you, you have come to the right place. I seek to, at least for my own personal development, to document how I fell in love with R. The question always is, why R? For speed? C/Cpp with relevant libraries will be blindingly fast. For ease of use? Let us not kid ourselves, the most popular and widely used statistical software is Microsoft Excel (If you are just beginning your jouRney, Python is a viable, robust, and widely accepted language that, I believe, is more flexible for you everyday use). Yet R harnesses decades of development and the open source community to provide standard methodology to whatever statistical task is needed. You want to use exotic statistical methods? Functions and libraries probably already exist. Most of the time, the hardcore statistical methods are available to you (the trick, usually at first, is to massage and comfort your data to input into functions).

Here I will explain how you, within a few months, can learn the lingo and start getting comfortable with R. I assume you have little to no programming experience. (If you are a MATLAB user, you will have an easier time). If you come from the C-family, you will have to get used to vectorized functions and the diminished use of loops (again, if you have experience in generic programming like STL you should get over this hurdle easily). Overall, my target audience is the budding undergraduate or early graduate student who wishes to learn R. I will provide books, tips, tricks to allow you to get up to speed. 

The next series of posts will hopefully help you:

1) Know the history of the R language and environment
2) Get started using R
3) Read data into R
4) Fit linear models
5) Fit generalized linear models
6) Navigate the growing number of R books available
7) Learn some R tips & tricks
8) Learn some general programming tips & tricks
9) Pick useful R packages
10) Know your online resources

A word of warning before we begin. I am no R guru. I would consider myself still a novice. I have approximately two years of experience with R. I still remember quite well how difficult it was when I first used R when I was an undergraduate, hopefully this material will aid in your development. Keep in mind, the only way to learn a language is by practice and knowing that this is a learning experience. Analogous to climbing a mountain. At first you may have a hard time breathing in the rarefied atmosphere, but the further you push yourself, your lungs will be quite adept.

No comments:

Post a Comment