Join Conrad Carlberg for an in-depth discussion in this video Download and install R's base package, part of R for Excel Users.
- [Voiceover] If you're going to start using R as the basis for your statistical analyses whether in addition to Excel or to use it in place of Excel, you're going to need to have the R software downloaded onto your computer. And that's what this lesson is going to be about. Before we actually start doing that though, I want you to learn something a little bit more about the system that you're using. If you come down to the lower left corner of your window and click the Start menu, assuming that you're using Windows 10, you'll get this window.
If you're using something such as Windows 8, you might have a charms bar at the right edge of your screen. And either way, you're gonna want to come down to Settings and then click System. And notice in the navbar on the left side of the screen, there's an About link, and you can click that. And once it has responded with a new window or a new pane, you can notice the system type entry under PC at the top of the screen.
And this particular system is a 64-bit operating system. Make a note of whether it's a 64-bit system on your computer or a 32-bit system because that will have some implications for just how you go about installing R. Once you have that information about the type of system that you are using, you're going to want to use a browser to get to this website here. It's named cran.r-project.org, and that's kind of a cryptic way of saying the Comprehensive R Archive Network.
And once you've gotten there, you have some choices for download. You could download R for Linux, R for the Mac, or R for Windows. I'll go ahead and use the Download R for Windows in this case. And we simply click that option and we get to R's subdirectories, one of which is Base. Now R comes with a Base system which has some degree of statistical functionality built into it and quite a bit of data handling functionality. That's what we'll be downloading to begin with.
You get the rest of R from the contributed packages, and we'll be getting to those later on in this series of lessons. At this point, you want to click install R for the first time at a link located in the upper righthand corner of your screen. So I'll click that now, and we get to the download page. The option that we're going to select is Download R 3.3.0 for Windows. That's the current release as of the time that I'm recording this. By the time that you're viewing it, they will probably have come out with a different release, and so it won't say 3.3.0 but something else.
That's nothing to worry about, perfectly natural and normal. You can also go to some of these frequently asked questions available on this page if you want to check on whether or not R runs on the particular version of Windows that you're running, for example. But at this point, we'll just click Download R 3.3.0 for Windows. And the download starts, and it's going to take a few seconds to complete. And when it is completed, we can go ahead and click on that button. And at this point you may run into a window that asks you to authorize the installation of R.
And you can go ahead and click yes. If that doesn't work for you for some reason, you'll probably want to get in touch with your tactical support staff to make sure that the version of the operating system that you're running will accept R and allow it to be installed. We're going to use the default command here for English as the language for the installation. At this point, we have a brief wizard, a fairly standard one for installation. And I'm going to choose options which install the default selections.
But go ahead and take the time to examine the information that's presented to you and make whatever choices seem most appropriate for your situation. But I'll go ahead and click Next now and it'll bypass the public license. And I'm going to accept the default installation folder and click Next. At this point, you have a decision to make. If you're running a 64-bit system, then you will want to include the 64-bit files. If you're not running a 64-bit system, if you're running a 32-bit system, you may as well go ahead and clear that box.
That it, at the very least, save you a little bit of disk space. The issue here is how much memory that R can access. And if you're going to be pumping huge amounts of data through R, and you have a 64-bit system, you'll probably want to accept it. But for the time being, I'm going to go ahead and clear that box and click the next step. And yeah, we'll go ahead and accept the defaults. And we'll want the shortcut in the Start menu folder. We'll also want to create a quick launch icon as well as the Desktop icon.
And click Next. And now the installation goes ahead and does all the extraction of the files for Windows. This really only takes a few seconds. And we click Finish to exit setup. And at this point, we can go back to the Desktop. There's our link to R and up comes the R Console. You'll be seeing a lot of this Console over the next few lessons. And now with the link to R on the Desktop, we could just double-click it and up comes the R Console. And you'll be ready to start processing in R.
Much of the course focuses on how crucial statistical tasks and operations are done in R—often with the DescTools package—as contrasted with Excel's functions and Data Analysis add-in, and then scales up from there, showing R's more powerful features. Conrad Carlberg will help you effectively toggle between both programs, moving data back and forth so you can get the best of both worlds. Start by learning how to install R and the DescTools package, and the data files used in all the hands-on exercises. Then learn about calculating descriptive statistics on numeric and nominal variables, and running bivariate analyses in both Excel and R. In the "Next steps" video, Conrad breaks down the pros and cons of Excel vs. R and provides tips for learning more about statistics in each application.
- Installing R and DescTools
- Descriptive statistics in Excel and DescTools
- Moving data between R and Excel
- Running the Desc function
- Bivariate analysis in R and Excel