 Hey everyone, welcome back. It's Veronica Howard. So I'm going to give you a series of videos here to understand the basics of visual analysis. I'm going to be giving you the Miller method. It is very rudimentary. It just gives you the basic principles of how we look at and understand our data. Visual analysis is probably one of the most, if not the most, important skill to take away from this class. If you're interested in understanding behavior analysis, you need to understand how behavior analysts evaluate their data. This is a topic where you really want to spend some time and make sure that you understand what you're doing. If you need additional assistance, make sure that you're reaching out for help. But this is a foundational skill and you want to understand this. You want to be solid on this before moving forward. So I mentioned before that behavior analysts use visual analysis to determine the effects of our interventions. Now we have some general guidelines here and Miller's guidelines are actually very rudimentary and they're very simple to understand. There may be a little bit more stringent and there are more nuanced ways of understanding, but Miller gives you a very, very good start. Visual analysis is pretty easy. Anyone can learn this skill, but it has to be practiced. So definitely make sure that you're using your time here. Note also that Miller's methods are very, very simple and it's a good place to start, but this language that we're going to be using here, this idea of divided and stable, convincing data, determining cause, those terms may be slightly different in everyday practice. So modern behavior analysts use slightly different terms. I'm going to give you those terms so that you understand them as well. And I want you to be able to kind of compare and contrast how those terms are similar. I'm going to throughout here make sure that I'm using Miller's language as much as possible than also trying to translate that into the way that most behavior analysts would talk about this information.