 I want to thank you for joining me in SPSS and introduction. And we'll conclude by giving you some next steps, things that you can do next, because you know, once you get through this, it can be a little confusing, feel like things are going everywhere. And it may not be totally clear where you should go. Well, here at data lab dot CC, we've got a few opportunities for you. First, of course, is more SPSS, we have additional courses on data preparation on data visualization, on statistical analysis and other topics that you can use to expand what you've learned in this introductory course and work on your own data. Now, if you've liked what you've learned with SPSS, you may want to try branching out to some other languages. The statistical programming language are and the general purpose programming language Python are very common powerful tools in the data science community and analytics in general. They're a great way to expand both the things that you can do with your analyses and your employment opportunities. And so I strongly encourage you to take a look at the courses on our Python at data lab. Next, we have specific courses on data visualization, one of the most important things you can do in getting to understand your data. SPSS can work well in those as well as other programs. And then I'm going to mention one final thing here. SPSS is a wonderful program. But it still has a fair amount of bugs and it can also be very expensive. Fortunately, some really interesting work recently in the open source community has developed a program called JASP, it's actually pronounced JASP, which is sort of an open source version of SPSS. It runs very differently. I find it very easy to use. And it makes it reproducible. It makes it easy to share. It's got some tremendous advantages. And we have courses on JASP here at data lab. I suggest you check those out and see how well that program is able to fulfill some of your computing needs. That being said, there are some things missing. What's missing exactly? Well, SPSS doesn't have a really strong and active user and developer community the same way that languages like R and Python do. But if you're creative, you can get around that. Academic conferences, meaning specifically, topical academic conferences like biology or management or the social sciences, they often have very dedicated SPSS users and teachers and may sponsor specific hands on workshops for learning more about SPSS and how can use it within your particular domain. But no matter what you do, I'm going to encourage you to simply get started, go exploring and see what you can do with SPSS in your own day to work. Thanks so much for joining me and happy computing.