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Page: R you ready for R?

In addition to reviewing this Page, you might find it useful to read my "Getting Started in R" document, which offers useful background on R and RStudio, as well as step-by-step instructions for getting up and running.

Download R Links to an external site.(link provides a list of sites that host the R software; try Duke or Washington University) and RStudio Links to an external site.-- R is a free (open source) software environment for statistical computing and graphics. RStudio is an integrated development environment that is easier to operate in than R and is perhaps the most popular way for people to use R. You'll need to download both, but my recommendation is to use RStudio. This blog post Links to an external site. provides a helpful talk through of both R and RStudio. 

Although working in RStudio and learning/using R code directly may be the most gratifying, it can also be somewhat challenging. If you're struggling with learning the coding language, you can explore some of the Graphical User Interfaces (GUIs) that have been developed for R. They are reviewed here Links to an external site., with links to their respective reviews and sites. Some of them offer more traditional point-and-click menu systems, along with the ability to see the corresponding R code. You may find BlueSky Links to an external site. (mirrors SPSS) and R Commander Links to an external site. to be the most familiar. In the end, though, I recommend trying to make a go of it with RStudio. There's value in learning to work with the code directly.

Here's a good walk-through of how to get started with R and RStudio Links to an external site.. 

Generic R Commands

You can find my generic R scripts (Word documents) for various tests here. 

Helpful Resources

These are some readings and websites that I found to be quite useful in getting to understand and learn R.

 

Very Useful Packages

R makes use of "packages" that users write to either accomplish new tasks or accomplish old tasks better. There are thousands of packages. Here are some of the packages that you are likely to make heavy use of.

  • tidyverse
  • car
  • haven
  • psych
  • ggplot2
  • dplyr

 

Data Visualization with R

Much of what people are looking to do with data is to understand it better through visualization. The following resources will help you develop proficiency with data visualization in R.