 Let's finish up our discussion of coding and data science, the applications part of it by just briefly looking at some other software choices. And I'll have to admit, it gets kind of overwhelming because there are just so many choices. Now, there's an addition to the spreadsheets and Tableau and SPSS and JASP that we've already talked about. I mean, there's so much more than that. I'm going to give you a range of things that I'm aware of. And I'm sure I've left out some important ones or things that other people like really well. But these are some common choices and some less common but interesting ones. Number one, in terms of things that I did not mention is SAS. SAS is an extremely common analytical program, very powerful use for a lot of things. It's actually the first program that I learned. And on the other hand, it can be kind of hard to use. And it can be expensive. But there's a couple of interesting alternatives. SAS also has something called the SAS University Edition. If you're a student, this is free. And it's slightly reduced in what it does. But the fact that it's free and also it runs in a virtual machine, which makes it an enormous download. But it's a good way to learn SAS if it's something that you want to do. SAS also makes a program that I really love where it's not so extraordinarily expensive. And that is called jump. And it's a visualization software. Think a little bit of like Tableau how we saw you work with it visually and this one you can drag things around. It's a really wonderful program. I personally find it prohibitively expensive. Another very common choice among working analysts is Stata. And some people use Minitab. Now for mathematical people, there's MATLAB. And then of course there's Mathematica itself, but that's really more a language than a program. On the other hand, Wolfram who makes Mathematica is also the people who give us Wolfram Alpha. Most people don't think of this as a stats application because you can run it on your iPhone. But Wolfram Alpha is in fact incredibly capable. And especially if you pay for the pro account, you can do amazing things in this including analysis, regression models, visualizations. And so it's worth taking a little closer look at that also, because it actually provides a lot of the data that you need. So Wolfram Alpha is an interesting one. Now, several applications that are more specifically geared towards data mining. So you don't want to do your regular, you know, little t tests and stuff on these. But there's rapid miner. And there's nine and orange. And those are all really nice to use because they are control languages where you drag nodes onto a screen and you connect them with lines and you can see how things run through. All three of them are free or have free versions and all three of them work in pretty similar manners. There's also Big ML, which is for machine learning. And this is unusual because it's a browser based it runs on their servers. There's a free version, although you can't download a whole lot doesn't cost a lot to use Big ML and actually is a very friendly, very accessible program. Then in terms of programs, you can actually install for free on your own computer. There's one called SOFA statistics. That means statistics open for all kind of a cheesy title, but it's a good program. And then one with a webpage straight out of 1990 is past three. This is paleontological software. On the other hand, does do very general stuff, it runs on many platforms, and it's a really powerful thing and it's free, but it is relatively unknown. And then speaking of relatively unknown, one that's near and dear to my heart is a web application called stat crunch. It costs, but it costs like six or 12 bucks a year. It's it's really cheap. And it's very good, especially for basic statistics and for learning, I used it in some of the classes that I was teaching. And then if you're deeply wedded to Excel, and you just can't stand to leave that environment, you can purchase add ins like Excel stat, which give you a lot of statistical functions within the Excel environment itself. That's a lot of choices. And the most important thing here is don't get overwhelmed. There's a lot of choices, but you don't even have to try all of them. Really, the important question is what works best for you and the projects that you're working on. There's a few things you might want to consider in that regard. First off is functionality. Does it actually do what you want? Or does it even run on your machine? You don't need everything that a program can do. I mean, think about all the stuff that Excel can do. People probably use one 5% of what it's available. Then there's also ease of use. Some of these programs are a lot easier to use than the others. And I personally find that the ones that are easy to use, I like them. And so you might say, No, I need to program because I need to do custom stuff. But I'm willing to bet that 95% of what people do does not require anything custom. Also, the existence of a community. Constantly, when you're working, you come across problems, don't know how to solve it and being able to simply get online and do a search for an answer and have enough of a community that there are people there who have put answers up and discuss these things. Those are wonderful. Some of these programs have very substantial communities. Some of them, it's practically non existent. And you get to decide how important that is to you. And then finally, of course, there's the issue of cost. Many of these programs I mentioned are free. Some of them are very cheap. Some of them run on sort of a freemium model and some of them are outrageously expensive. So you don't buy them unless somebody else is paying for it. So these are some of the things that you want to keep in mind when you're trying to look at various programs. Also, let's mention this, don't forget the 8020 rule, you're going to be able to do most of the stuff that you need to do with only a small number of tools, one or two, maybe three will probably be all that you ever need. So you don't need to explore the range of every possible tool. Find something that does what you need, find something you're comfortable with, and really try to extract as much values again out of that. So in some in our discussion of available applications for coding and data science. First, remember, applications are tools, they don't drive you, you use them, and that your goals are what drive the choice of your applications and the way that you do it. And the single most important thing is remember, what works for you may work well for somebody else. If you're not comfortable with it, if it's not the questions you address, then it's more important to think about what works for you and the projects that you're working on, as you make your own choices for tools for working in data science.