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R is the language of big data—a statistical programming language that helps describe, mine, and test relationships between large amounts of data. Author Barton Poulson shows how to use R to model statistical relationships using graphs, calculations, tests, and other analysis tools. Learn how to enter and modify data; create charts, scatter plots, and histograms; examine outliers; calculate correlations; and compute regressions, bivariate associations, and statistics for three or more variables. Challenge exercises with step-by-step solutions allow you to test your skills as you progress.
The first thing we need to do is we need to install R onto your own computer. Now R is a free download. It's available for Windows, Mac, Linux computers and installation is a simple process. The first thing you need to do is you need to go to the website r-project.org. You can actually download it from a number of places, but this is the central location. Now if you scroll down a little bit, you'll see that they have version 3.0.1 is currently available. I want to make a brief note about versions and R.
Version one was released in February of 2000 and version two was released in October of 2004, four and a half years later. Version three was released in April of 2013 so that's a nine year gap. On the other hand, the versions are almost identical. The functionality, the interface are almost identical. Really, the biggest difference between three and two is that three is an accumulation of things, the most important of which is 64-bit support for all platforms in which case, you also support for parallel processing and other things.
But functionally. They're identical. In the day to day, you would not notice the difference. So, you don't have to worry about getting a new version that completely out dates all of your existing work. Anyhow, we're going to go and download version 3.0.1. So just click on Download R. And then you get to pick a mirror. And by the way, CRAN stands for the comprehensive R archive network. And all of the information is duplicated at all of these locations. So pick one that's close to you or not. I'll go to U.S.A I am close to Berkeley. And so, just click the one that you want.
If you're on a Mac, you just want to click and choose this top one. That's the package, the binary. If you're on a Windows computer, choose the base. And if you're on Linux, it's going to depend a little bit about which distribution you're using, but, if you're a Linux user, then you know what this all means and you know how to deal with it. But choose the one that you want and install it on your computer. From there, you can launch it. To launch it, just double-click on the icon, and this is what you get. I'm going to make this bigger. R is a command line application and well technically, R is a programming languages and this environment is a way of working with the language.
Now, it's all command line and you type one thing after another. It is possible to add drop-down menus. But mostly, you're typing out here. And it's going to look mostly the same from one platform to another. We're going to talk about one particular program that we're going to lay on top of it called RStudio. Which will give it a completely consistent interface from one operating system to another. As well as provide a number of things that make it easier to work with R. But this fundamentally is the program. We've downloaded it, we've installed it. And we've got it up and running now.
Now, I thought I would just mention one other thing before we go and it's about the name of the program, R. R is an implementation of an earlier programming language called S, which was for statistics so from S to R. Also the creators, Robert Gentleman and Ross Ihaka are both R's in their name, so that's where we get R. It's just a little bit of an origin story for the program. If all went well then you should have a fully functional copy of R on your computer by now. In the next movie we'll look at another piece of software that I mentioned called RStudio, that will help make life with R a little bit easier.
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