 Hello, welcome to our Introduction to Statistics course. Regardless of how you got here, the URL, the address for this site is stats.profreedman.net. You might want to bookmark that so that you can get to the page or the site anytime you want. This is a site that's free and open to the public. You may be using it as part of a course. You may be using it on your own because you want to learn statistics or even refresh your knowledge of statistics. However, it was that you got to us, welcome, we're happy to have you. Here's the other Professor Friedman to tell you a little bit more about it. Okay, let me go over the objectives of the course. You can see it on our website, what are the objectives of the course. You can see that we're going to teach you how to summarize data. You'll learn about descriptive statistics. You'll learn about inferences and we call that inferential statistics. We're hoping that by the time you finish the course, you'll know the difference between junk science and real science today, as you know, statistics is very important in making that distinction. And also we're going to be teaching you how to use Excel to analyze data. And you'll see that there's a way to teach yourself a little bit of Excel. You don't need too much, but we will be using Excel in the course and we're going to teach you some statistical techniques such as Z-Tests, T-Tests, you'll learn a little bit about F-Tests, Correlation and Simple Regression. You'll learn about one sample and two sample T-Tests and one sample and two sample Z-Tests. So this will be a fun course. Again, we try to minimize the memorization, very little memorization because we're going to allow you to use formula sheets and we especially want you to get comfortable using Excel. So it will be a lot of fun and very useful when you look for a job in the future. And back to me, alright, sorry about that, technology, okay. I want to sort of help you navigate around this site a little bit. Everything is pretty clear in the left navigation pane. We're going to get back to this overview of the lectures. I actually like that a lot, but we're going to go look at the topic by topic first. Here's our, this is the box of our course materials. Topic by topic is basically the lectures in a nice, beautiful, flashy, individual lecture topic by topic way. Personally, like I said, I like this one, even though it's a little bit more boring and plain vanilla, but it lays it out very nicely. You've got all the topics and you can see much more clearly, I think anyway, in this simple table. For each topic, you've got lecture notes in PDF format. So if you like, you can just print it out and study it on your own. You don't have to be connected to the internet. You've got the same information now in lectures on PowerPoint. The links that say lecture are basically narrated PowerPoint. So you can advance slide by slide, go faster when you can, go slower when you need to. These YouTube links are the narrated PowerPoint lecture just wrapped up as an MP4 and exported from PowerPoint and stored on YouTube. So you can stream it anytime you want. All of these, the PDF, the PowerPoint, the YouTube videos have the same information or they should. Then for each topic, you also have a couple of very, very tiny exercises just to test your knowledge. We call them do it now and then each one has its own solution. This way, you get a chance to firm up your knowledge of a subject area before moving on to the next topic. So going back here, we've seen topic by topic. Readings are probably less important right now than at the end of the course because basically what you've got is some very interesting books that you may want to take to the next level and also some interesting workbooks that you may be interested in. Online resources, you may find them interested. I wouldn't say it's an integral part of the initial course. For the course itself, we're interested in the lectures topic by topic or overview of the lectures here. The handouts, the virtual handouts which we will talk about soon and the homework assignments and I'm going to give you over to my better half for that. You heard them, the better half. Let's look at the homework assignments. Here are the homework assignments. Now this is very important because you're going to have to submit this, these assignments, at least if it's one of the freedmen's, you're going to have to submit it in blackboard and we check to see if you've done them. Notice how the homework assignments are laid out. After you view the lecture, the first lecture deals with measuring data, you see there's a homework and you're going to do it by hand and there's a solution so you can check how you've done the homework but you're going to have to submit the homework. Best way is you take a picture of it, the PDF, you submit it as an assignment in blackboard and you see we cover the whole course and these are usually about well some have more than five, six problems, some have more but you know you do the problems and this way you're going to learn everything there is in the course including measuring data, descriptive statistics, single variable, descriptive statistics, two variables, etc, etc, chi-square we're not doing this semester so forget about that but we end with simple linear regression. Again, chi-square, I don't know if the other professors are going to teach it but we're not teaching it. You see all your homeworks are here so when you hear the term homework, this is what you're going to have to go to, to this side called homework, do the homework, take a picture of it, do it by hand, take a picture of it and then you submit it in blackboard and also check the solution, the solution is there. Me again, so this is a very interesting exercise in transparency is what I think about it as. In many statistics classes, the basic idea is here's your homework, each problem has only one correct solution and I'm not telling you about it until after you give in the homework. Over here what do you have? You have all the homeworks and all the solutions up front. You can use this course for independent learning and even in our case, both Professor Friedman's, we have the same idea towards homework. You really are doing this independently for yourself. If you do your homework, check the solution and you can't see your way clear to how did we get that solution? It's so different from yours. That's the time to email your professor and say, can I have some time to meet with you? There's something I don't understand here. You're using this as a guide, but in my opinion, I kind of like the idea that you've got everything laid out through the whole semester, even the solutions. There are no secrets here. Full transparency. One section that I wanted to go over and just briefly go over it because we're sort of running out of time. Handouts. This is sort of the equivalent of what you might get as handouts in a face-to-face class. The formulas don't ever let me catch you memorizing. You're not supposed to memorize anything. Formulas are things we look up. We're not supposed to have to remember them. We're geniuses, but we're not that kind of a genius. We're not computer databases. We're human beings. You look formulas up. Tables also. On any exam that's in class, at least my students, you'll be getting the formulas and tables. And anytime you take an exam online, if you're doing this independently, you're going to bring that along with you to the exam. So here are some other tables that you'll find useful. Better yet, if you take a look at the prep for exams section, see this formulas and tables? That's everything that you're going to need for this course. If you're taking any exam in the course, let me just click on it for a minute. There you go. And you can print this out and use it whenever you take an exam. Okay, back to the handouts. Maybe the most interesting thing here is that this isn't only a course in pencil and paper statistics. We very much want you to learn to use Excel. And I got to say that these instruction sets for Excel, you're not going to, it's not a whole Excel course. You're not going to become an Excel expert. But these are pretty dummy proof. Believe me. Take my word for it. I've used them myself. And sometimes, if I haven't used it in a long time, I have to go back to these instructions to do the statistical test. But it will make you familiar. It'll make you comfortable using Excel. And you'll be able to learn it better after that. And certainly you'll be able to do the statistical analysis that you need to do for this course. These are really, really nice video tutorials, if I say so myself, also for Excel. And eventually, when we do it, when we talk more about the exams, we're going to talk more about what these are. But you basically have a bunch of notes, study sheets that were taken from the lecture notes. That's what these are. A few review sessions, practice problems. We don't have an actual practice exam. But that's because we always believe that practice should be more than what you're going to have on an exam. So you just have lots and lots and lots of practice problems. You don't need, you don't need the specific for Baruch section of the handouts. Okay, and then finally, let me give you back to the other professor Friedman. Well, like all courses, there are some prerequisites. Again, these are very simple prerequisites. Like you should know a little bit of algebra, right? Simple algebra. We're going to be using summation notation. In fact, if you use Excel, you see there's a big sigma for summation. And that way, you explained it all, the things you need before you take the course, just to brush up on algebra. Now, the algebra is like, I think I learned it 9th or 10th grade. So it's nothing more complicated than what you did in high school. Again, 9th grade algebra, maybe 10th at most. So that's all in the boot camp. So we recommend that you go through it quickly. You may find that you know it all. Yeah, I'm going to click on boot camp. And you see it even tells you what we're going to do. What are weighted averages, which many of you know, the term expected value, how to work with a proportion, a fraction, factorials, you have to know that, you know, five factorial means five times four times three times two times one. Okay, that's you know, factorials, how to solve for X, you know, one unknown and one equation, how to analyze what a straight line is and how to do that on a graph. These are things we're going to do in the course. Again, you've learned it all in high school. You've gotten it possibly, but go through it quickly. In fact, I would recommend you do this before the course starts. And we call that boot camp. And I'll give you back to the oh, we can end here. I just say you'll give you back to the other Professor Friedman. I'll say goodbye here. I'm sure we'll be seeing each other again pretty soon.