 Hello, welcome to our site and learn Introduction to Statistics course. However you got here, you're welcome. We offer this free to anyone who can get to our Google site. It's available free on the internet. We believe the internet wants to be free, so it's not ever going to be up in back of a paywall. Indeed, our own students use it. You may be here because you're starting class soon and you want to see what this is all about. This is what we call our first day getting started video. Just introducing you to the course site and how best to use it. I'm Professor Linda Friedman. I'll give you over to Professor Hershey Friedman and he's going to continue and I'll get back to you. Let me tell you about the objectives of this course. Things that you're going to be learning. You can see it on our screen here. First you'll learn how to summarize data. We call that descriptive statistics. You'll learn about inferential statistics. Hopefully by the time you finish this course you'll know the difference between junk science and real science. You'll also learn how to use Excel. We have quite a few handouts on Excel for data analysis. You'll be comfortable with Excel by the time you finish this course. Basically, we're going to get you comfortable with numbers. And remember, this course is almost no memorization. So we want this to be a fun course. Let me give you over to my partner right here. All right, back again. Let's navigate here a little bit. We've been on the home page and go to the left-hand side navigation pane. The website, by the way, if you've seen it before, it has a nice new look thanks to Google who forced us to migrate to new sites. This is the year 2020 when such things happen. We're going to skip Bootcamp because that's really before you start the course and we'll get back to it. In my opinion, the best way to start learning statistics from this course is to go to overview of lectures. There we are. And what you see is the topics from a start to finish of a typical introduction to statistics course. Each topic has its own set of notes. The notes are just PDF files, print them out, put them in a loose leaf binder and take them with you when you're not in an internet area. Everyone studies a different way. Some people like to read. If that's you, you're going to like the notes. Over here we've got actual lectures. The lecture link is a PowerPoint set of slides. Each one is narrated. So you can advance on your own, go fast, go slow, repeat, pause, do a problem, come back. You're more in control. This YouTube link is exactly the same thing. It's just that PowerPoint, so nicely, allows us to export the slides with narration as an MP4 and then we just put it up on YouTube so that you can stream it. Some people, after a while, when they're reviewing for the exam, like to just run the YouTube videos while they're doing something else. Just listen to the lecture while they're doing other things. And I have found from students talking to me over the years that if you're having trouble remembering concepts, that's one way to help you study, let's say for the comprehensive final, if you have one at the end of the semester. Then we've got, for each topic, a very small set of exercises that we call test your knowledge. And this is the do it now link. And all it is, is I did the lecture, I know the material, I want to make sure it sticks. So I'll do a couple of problems. And then, of course, this is not your actual homework. This is just exercises to test your knowledge and make sure that you keep that knowledge. But what do you do after you finish the lectures? You go to homework assignments over here on the left hand side in the navigation pane. And let's go over to the other professor Friedman. Well, the way to really learn statistics, and we keep telling this to students, just do problems. The more problems you do, the better you get until this becomes just natural to you. All right, and notice the way it's set up. You know, for each topic, measuring data, our first topic that we teach you in the course, notice that homeworks and also the solution is right there. So don't go to the solution first. Go to the homework, do the homework by hand, take a picture of it, and you're gonna be submitting the homeworks in blackboard. And each professor's gonna do it differently, but they'll tell you how they grade this or whatever. But the reality is you have the solution. This transparency in this course, you can see the solution because we expect you, those of you who wanna learn by yourself can do that too. Of course, your professor will help you a lot. And if you can't do the homeworks, that's the job of the professor, to show you where you're going wrong. But again, you have the homework, do it, take a picture of it, send it in blackboard. Those are called homework assignments. And then of course, you know, you've got the solution there. Here's my partner again. So basically, we don't keep any secrets here. In a lot of cases, you do, given a problem to do, and nobody wants to tell you the answer. It's not in the back of the book. You have to wait till the teacher comes back a week, two weeks. No, it's all here. We believe in transparency, all laid out for you. Let's see what else we got here. Handouts, our page of virtual handouts. You use them as you need them, obviously. Firstly, very important, formulas and tables. If you're doing this on your own, or if you're one of our students, if we're doing this in a face-to-face class, if you're doing this online in an online class or a hybrid class, this is what you need. We don't want you to memorize anything. I just clicked on this so you can see what's in here. It's a packet, which you can print out if you need it, and it's a good idea to do that, so you get used to using this and looking things up when you're doing your homework. You've got a couple of pages of formulas. Never, never, never memorize a formula, not in this class. And I'll tell you what I tell my students when we do this introduction face-to-face. If I ever catch you memorizing a formula, I'm not only going to take off points from your next exam, but in a few years, when your kids come to me and are taking a test, they're losing points too. It's really funny, right? I got that from the other Professor Friedman. I steal his jokes too. Okay, and these are various tables that you might use to look stuff up. Obviously, you're not going to be memorizing those. Let's go back to the course. Excel, a very, very important part of the course, a very important part of the course is Excel. You're not going to become an Excel expert, but these are really, really handy guides so that you can sit down at your computer and do the work. You don't have to feel lost. All you have to do is follow step by step. And just by doing it, by experiencing it, you're going to become familiar and fluent, or maybe a little bit fluent in Excel. And if you want to take this further and do advanced Excel work, you'll have the foundation for it. And this is the same, well, it may be even better. These are print, these are PDFs, and these are video tutorials for using Excel in an intro stat course. This is less important at this point, but when it comes time to review for the exam, you'll have a lot of resources on this page. Practice problems, review sessions, study sheets. It's all here. I'm going to give you over to my partner. Before you actually even take the course, it's a good idea to go to the boot camp. Okay, we expect you to do this before the class starts, but mostly you don't even need it because it's really a review of the algebra that you probably learned in ninth or 10th grade in high school. You can see what's in the boot camp. We have summation notation. So you can learn about summation. Some of you use Excel, see that big sigma, which means some, a column or some a row. The summation notation, weighted averages, expected values, learning, reminding you how to use fractions, proportions, percentages, factorials. Remember what a factorial is? Like 10 factorial. That means 10 times nine times eight times seven times six times five times four times three times two times one. Remember that? That's called a factorial. You learn how to solve for an unknown when you have an equation. That's a ninth grade algebra. You also learn about a straight line and what a slope is. This is just refreshing your knowledge. You will need this in the course. But again, if you need a refresher, instead of taking a whole prerequisite in algebra, which is kind of ridiculous, just do the boot camp. Some of you will go through it one, two, three, it may take you 20 minutes. Say, oh, I know all this. And those of you who don't remember things, go review. You don't need a whole prerequisite course, but this you do need. Just make sure you know the basics. And back to my partner. Yeah, I'm just here to say goodbye. It's been a nice meeting you in cyberspace. We both look forward to hearing from you, working with you. And I hope you enjoy taking the statistics course.