R Week: Getting Started with R by David Keyes

Hi, I’m David Keyes, founder of R for the Rest of Us, which helps people who think of themselves as “typical” R users learn this incredible tool. R has a reputation for being difficult to learn, but there are some ways that you can get up and running quickly. And, even if it takes you a bit to learn, it is worth it in the end. Using R will save you time and money. What’s not to like?

When most people say R, they are really referring to two separate programs. R on its own is a text-based program that offers the underlying functionality of the software. Most people use a graphical user interface (GUI), which makes it much easier to work with R. RStudio is by far the most popular GUI. To start working with R, you’ll want to download both R and RStudio.

Screenshot of RStudio
RStudio

Rad Resource: If you want some guidance on getting set up, check out Chester Ismay and Patrick Kennedy’s free book Getting used to R, RStudio, and R Markdown or the free Getting Started with R course I’ve put together.

Hot Tip: Starting out, I strongly recommend using what’s known as the Tidyverse. This collection of packages all share an easy to understand coding style and provide the vast majority of the functionality you need to import, clean, wrangle, analyze, and visualize your data. And tidyverse packages are not just for beginners — they are among the most popular packages in the world of R

Rad Resource: To get started using R, I would recommend starting with the RStudio primers. These interactive tutorials will teach you the basics of working with your data. RStudio has also recently developed an education section of their website, which has links to other beginner-focused learning resources

Most people think of R as a direct replacement for whatever tool they currently use, but many people find R to be even more powerful than other tools. For example, RMarkdown, which I’ve called R’s killer feature, enables you to go from data import to final report, all in R (a post later this week by Dana Wanzer will show you how this works!).

Rad Resource: Once you get the basics under your belt, the best place to go next is the free R for Data Science book. Considered the Tidyverse bible, it lays out an integrated approach to working in R at all stages. 

One of the great things about learning R is that its users are extremely welcoming. No matter how basic your question is, R users are happy to help. Two great places to ask for help are: 1) on Twitter using #rstats, 2) the R for Data Science online learning community.

The American Evaluation Association is celebrating R Week with our R-forward colleagues who have contributed all of this week’s aea365 posts. Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org. aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

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