There are multiple ways to interface with R. Some common interfaces are the basic R GUI, R Commander (the package “Rcmdr” that you use on top of the basic R GUI), and RStudio.
When I first started to learn to use R, I was bound and determined to use the basic R GUI.
As someone who was already used to programming in SAS, I wasn’t looking for a point-and-click interface like R Commander. These kinds of interfaces are notoriously limiting when it comes to advanced analyses and software capabilities. (Though if I’m being honest, probably 95% or more of my daily tasks could be handled using R Commander).
Without knowing much about it, I also didn’t want to use RStudio. It seemed overly-complicated to download an additional software package for something that already functioned on its own.
One day though, when working with someone who wanted to use RStudio, I decided to download it and give it a chance.
I never went back to using the basic R GUI.
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If you are like I was for a long time, you have avoided learning R.
You’ve probably heard that there’s a steep learning curve, and that the available documentation is not necessarily user-friendly.
Frankly, both things are true, to some extent.
The best and worst thing about R is that it is open-source and there is no single company that is responsible for R or your ability to use it. While there is a developer community that maintains a set of standards and regulated documentation, anyone can add new functionality to R through user-created “packages.”
This gives R users a large, flexible range of options (once you know how to install the packages, of course!), which can be a major advantage.
On the other hand, these packages are as diverse as the users who create them, and they may emphasize different model features, output displays, and even basic methodological principles.
Underlying all of this, though, is what I feel is the truly intimidating part of R:
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