The R Project for Statistical Computing is a free, open source statistical computing language that is popular among researchers in many fields.
The learning curve for true understanding is steep, but specific tasks (e.g., importing files from other statistical software) are often quite easy because of packages that can be created by anybody. R undergoes rapid development and improvement. Tutorials even a year old may be out of date.
Note that RStudio is currently in the process of changing names to Posit. Various tutorials may reference one or the other, but both are acceptable at this time.
See the slides from our Getting Started with R (pdf) workshop for an overview and recommendations.
RStudio = Posit (the company is changing names)
Learn R in 39 minutes (39 min, Equitable Equations) - Good overview of getting started and key functions in R, but goes quickly and may use terminology some are unfamiliar with.
This book is one of the best resources and good to either read or refer to. However, non-programmers who want help with the very first steps should look elsewhere.
Are you learning R, but it just isn't making sense? Make sure you feel comfortable with Functions & Objects and related terms.
Functions in R are similar to those in any programing language, or in Excel.
Packages are the code for groups of functions. You must download them to your computer and load them into R to use them.
Some languages (and tutorials) call these "variables", but R's term is "objects" to avoid confusion with data variables.
It is a name given to some data, whether a single value, a group of values, or an entire dataset.
Objects have structures (is it a group of values or a data table?), and types (is it numbers or letters?).
Videos: Data Types and Structures (LinkedIn Learning)
Many people will ultimately learn both. But, they are similar enough that you do not want to learn them at the same time--it can get confusing to switch back and forth. Knowing either one will help you learn the other. So, just pick one and get started!
If you already know another statistical software or programming language, you might try these first.