Foundational Statistics for Data Analysis with Excel: Analyze Data with Excel

0:07Hello and welcome. My name is Jonathan Barrios and I'm excited to be your trainer for this course on foundational statistics for data analysis with Excel. In this first skill, we're gonna start off with data analysis with Excel, and we're gonna be talking about concepts. So let's check out what we're gonna learn in this first skill. All right, so we're gonna dive into data analysis with Excel. And in this very first skill, we're gonna talk about setting up Excel.

0:38And then we're gonna talk about using Excel for data analytics because it's not always the case where Excel is gonna be the best tool for data analytics and we'll dive into that a little bit more. And then we're gonna dive into the user interface just to open it up and get started and check out the ribbon and the file menu and things like that. And then we'll talk about the limitations, again, through example, and then we're gonna dive into data types and then some Excel formulas and some of the limitations and why we might need to use functions.

1:11And then we'll talk about the data Analysis ToolPak. And again, what the data Analysis ToolPak is, is added functionality to extend Excel's ability to perform statistical tests. And that's something that you add on and that's what we'll cover in that skill. And at the very end, there's a challenge that gives you the opportunity to apply everything that you've learned so far. All right, so that's it for the introduction. I hope this has been informative, and I'd like to thank you for viewing.

0:07Alright, in this video we're gonna jump into Excel and the context of data analysis, why you should use it in this course, and maybe why you would not use it. It's not generally my recommended tool for data analysis. And we'll talk more about that. And then we'll see how easy it is to get set up. We'll go to the Microsoft website and talk a little bit about the online version and the desktop version, the standalone version, and then we'll get started with Excel in the subsequent videos. All right, let's check it out.

0:38Alright, so Excel for data analysis. Alright, let's check this out. So when to use Excel for data analysis. You might be thinking, well, why don't I use it all the time? Well, there are many reasons why you wouldn't do that. It's generally not my recommended tool for data analysis. And there's many, many reasons. First of all, anything Excel can do, R or Python can do better and much faster. So R and Python are programming languages and we'll talk more about them in subsequent videos and that's just the first reason that there's a better way to do this.

1:15That's the first one. Number two is that it has row and column limitations. You can't really work with big data if you're working with Excel, so it depends on your application and where you're using Excel. And it's also not appropriate for historical data storage and we'll talk more about that, but that's another reason. And there's some companies that use it as a single source of truth and whenever there's some updating going on, it's very easy for data to get lost, especially when you're updating.

1:46So it's definitely not a good use for historical data in storing that data. Let's go back to these row and column limitations. So the rows we're talking about, I would say 1 million tops. And just because you can get a million rows doesn't mean that you're gonna be able to work with a million rows. Depends on your computer and the kind of data that you're working with. It can be very, very slow. And as far as columns are concerned, we'll have a top of 16,384, I think columns or something like that.

2:21And so there's a limitation on the columns as well. That's a lot of columns, and a lot of rows to be quite honest. However, it's gonna get very, very slow and sluggish whenever you start to get anywhere near that. Okay, and there are many other reasons why not or why you wouldn't use Excel for data analysis. And definitely I would recommend Googling it. For Pandas users you can see the Pandas documentation and Pandas is a open source library for Python that allows you to work with data and you can see comparison between Pandas and Excel.

2:57And I'll also link that documentation above this video if you wanna take a look at that. That might even help you get an idea of what Pandas is, right? So for Pandas users, this will give you an idea of Excel and vice versa. Alright, so I just talked about why it's not the best to use Excel. So why are we using it in this course? Great question. Well, first it's a great visual learning tool. When you're working with Pandas, it's a programming language, so you're gonna get code and you're not gonna be able to see things like you do in Excel.

3:32Excel is a very visual tool. It uses a graphical user interface and you can see what you're working on. Whereas with Pandas and programming languages in general, you're just typing code and something happens and you'll get an output. But a lot of that, what happens in Excel gets abstracted away. And that's kind of what I wanted to mention here. And it's also easy to use without much training. So that's why it's so popular. And again, not the greatest tool for data analysis, but it is ubiquitous and everybody uses it. It's hard to imagine an office that hasn't, that doesn't use spreadsheets in one form or another.

4:06And it's easy to share, not necessarily collaboration, but it is easy to share so that there is another plus there. And that's why we're using it because I can share these workbooks with you and it's still used today and it's good to know. So as I said before, it's hard to imagine an office environment that's not using a spreadsheet. So I chose Excel for this course because it's a great teaching tool, especially when it deals with analytics. I feel that doing this the slow way manually is a really great learning experience.

4:39For example, when you're doing a T test in Pandas or Python, you're just typing one line of code and then you get a P value, it just shoots it out, it's abstracting the process. But in Excel it's kind of cumbersome to perform statistics, but at least you go through every single step. And that's why I'm using it in this course because it's a great teaching tool. Alright, so again, it's not generally what I recommend for data analysis. So what am I talking about? Excel.

5:09Excel's not generally recommended for data analysis. However, we are gonna get a lot of use out of it in this course and in this scale. And we're going to dive into Excel and what is great about it, how to get some extended functionality out of it so that we can perform statistics using the analysis tool pack and so on. All right, so let's jump into Excel. And go to Microsoft Office website at office.com. And I will link this above the video, but it's basically office.com.

5:42And here you have some choices. So if you just sign in, if you have an account, great. If not, you might need to create an account. And you can also get a free version here. I wouldn't recommend using the free version and would instead recommend that you get a trial version for a month. So you can do that by clicking on Get Office. And let me just point out that whenever you do sign up for a membership or once you do have that free month trial to see if you wanna continue with Excel or not, you'll have the option of using Excel, not just as a standalone application, but also an online version.

6:23So there's two versions. There's an online version and a desktop version. So let's take a look at that now. Okay, so this is what we're gonna dive into in the next video, but I wanted to show you this workbook. And what is a workbook? Well, a workbook is what you see here, and we have two worksheets. One is called start and one is called solutions. And this is the online version, you can tell because it has this sort of green bar at the very top.

6:55And this is the standalone application version. And you can see it's gray at the top and not green. So that's the main distinction. So let's look at the difference. This one also has a little bit bigger. It looks a little bit bigger. It's at 160. This one's also at 160. It's not as big, but I could zoom it in even a little more by clicking on this plus arrow here, something like that. And that gets it a little closer, but as you can see, there are two different versions and they're slightly different. And you can't use the statistic analysis tool pack, the analysis tool pack that we're gonna install later.

7:31You can't use that here in this version, in the online version. That's why I recommend that you use the desktop version for this course. All right, so that's about it for this video. Just an introduction into why you would want to use Excel for data analysis and when that might be a good choice and when to maybe consider using a programming language or an analytics suite. And we'll talk about those in upcoming videos as well. All right, I hope this has been informative and I'd like to thank you for viewing.

0:07In the last video, we talked about Excel for data analysis and when it's good to use Excel for data analysis and when it's not. And why I decided to use it in the course. So we kind of got a general idea of what the pros and cons of Excel are and how there's an online version and a desktop version. Well, we're gonna do in this video is talk about the differences between the online version and the desktop version, and look at the ribbon, the spreadsheet areas of rows and columns, the limitations, and the different ribbons and how those work.

0:41And then the difference between the analytic tool pack, how it works on one version and not the other version. All right, let's get started. Okay, so we already talked about the online version, and this is the online version. And so the difference here is that you have this green tab at the very top. The standalone version, it's all gray at the top. And so that's the main distinction visually, right? And there are another distinctions, other distinctions. For example, if you go to data, and then you go to analysis tools, you have this analysis tool pack.

1:15We'll be installing this later so that we can perform statistical tests. Without this, you would not be able to do that, and here you do not have that data option. And that's because it's not available on the online version. It's only available on the desktop version. All right, so everything else should be the same though, more or less the ribbons are a little bit different. So let's take a look at the desktop version. So first we have what's hidden out of view is the file menu up here.

1:45So you have all of these file menus, which are sort of repeated in the ribbon. So I'm gonna show you this ribbon. So if you click on home twice, it'll go away. But if you click on it once, you'll see this ribbon pop up. And this ribbon is giving you a lot of great stuff. So first, what it's doing right about here, this is all for text basically. So we're working with text, and this is something that you would see on a text editor. And then you would see something here. These are for the data type.

2:17So you can change the data type. Let's say you have a number and you want it to be a percent, or you want to take some of the decimals off, right? So the rounding, you can actually do that here. And so this is a collection of different tools that are on the home because they're probably used the most. And here we have some conditional formatting and here's some more formatting. And then here you can insert different things, like you can insert a row or a column or delete them and do some formatting. And then here you have some filtering, and selecting, and auto sum, and clearing, and some additional tools.

2:54So let's take a look at each one of these. So that's the home ribbon. The insert ribbon has a lot of stuff. So right here we have pivot tables, and some tables, and you can add pictures, and some 3D objects. And then here you would have some maps and graphs, and things that you can add in. And because we're in the insert tab, and here you can insert some graphs or charts. And so you can click on recommended chart. Let's say we had, maybe if you click on this right now, it'll say, I don't know, there are no recommendations.

3:30But if you add some numbers here, 3, 3, 2, and we're just looking for any number right here. And then you highlight this, and then you click on recommended charts, then you'll see that it's recommending these charts, and you could say, "Well, I would like to have this one." And then it just builds that chart for you. Okay, so let's take that off, and let's delete these, and we'll move on. So what else do we have? Okay, so that's an insert. And so we were talking about recommended charts, and here you can add links, comments, and some text box, and some other things that you can insert.

4:06Draw is pretty straightforward, so if you want to draw something, well here you go. This is how you would do that. And you go to the draw ribbon and then give these options mostly highlighting and things like that. Page layout is very straightforward and is dealing with page layout. So background and margins, orientation, colors, fonts, and things like that. Formulas, this could be very helpful. I don't use this that much, but we'll get into formulas later and then we'll talk about that. So this is all just about formulas.

4:37So here we're inserting a function. There's financial, logical, text, date. And so these are functions that are put into different categories for ease of finding, and use, error checking and things like that. Then we go to data. And this is something where you can actually connect to data. So you can get data from somewhere else. You can also get data from a picture, you can refresh things, and you can also put in stocks or geography.

5:07So you can kind of change things up here. And this is the, since this we're in the data tab, you get a bunch of other things like sorting, filtering and advanced tools, text to columns, remove duplicates, which is very useful and we'll talk more about that later. And then you have this, again, the analysis tool pack. And this is something that we're gonna add so that we can do some things like T-tests and be able to perform AB and AB testing or AA and AB testing. Okay, so that is the data layout or data ribbon.

5:41Now let's look at the review ribbon. So here again, I don't use this too much, but you can protect your notebook here and your worksheet, and you can also look at your statistics and maybe use some spelling and things like that. So this is adding some comments, show comments and some notes. And the view tab, the view ribbon is pretty straightforward for view. And if you go here and you look at this, you're gonna see a lot of these repeated, right? So this is just giving you that visual sort of format that makes Excel so easy to use and accessible, right?

6:16That's probably why it's so popular. And then finally we have this tell me section where you can say, "Oh, I want a pivot table." Right? So I can just type in pivot. And before I'm done typing, it says pivot chart, pivot table. Cool, that's what I wanted. I click on that. So this tell me section is great when you don't know where something is. And that happens to me a lot. (chuckles) So I just keep it on the home tab. And also you have this quick access toolbar at the very top. So you can go home. If you click on that, it takes you to the home, so that you can grab some documents.

6:50You can also, what is this one right here? Saving, undo, and repeat clear. And if you click on this, three little dots, you can actually customize this. So you can add more commands, you can add sorting, ascending, descending, whatever you use the most. You can definitely put that in the quick access toolbar. And let's talk about the rows and column limitations. So we say that we have a million rows, let's prove it. Well, if I'm gonna use shift command down arrow, or what did I do?

7:22So command, command down arrow. So that takes me to the very bottom. And here we have 1,048,576 rows. If I use command and go back up, and I believe on Windows, I'm on a Mac. So on Windows you would use control down arrow. And now let's take a look at the max columns. If I use control right arrow goes all the way to the right and you get 16,384 rows. (chuckle) Or columns, I should say. And let's talk about how that works.

7:52Well, you have A, B, C, D, all the way to, it goes to Z. And then it goes to AA, AB, C, D, and it keeps doing that. And then it'll cycle to the next letter in the alphabet, which would B, so BA, B, C, and so on and so forth. And if I go to the very end here, we are on E, XE, and then XEZ, and then XEA, B, C, D, and then it stops on D for whatever reason, and that's the max 16,384.

8:23All right, so that's it for the user interface for Excel and checking out some of those limitations and the differences between the online and the desktop application version of Excel. And how you can install the stat, the analysis tool pack in the online version. It only works in the desktop version. In the next video, we're gonna cover data types. I hope this has been informative, and I'd like to thank you for viewing.

0:07In the last video, we talked about the user interface and the differences between the online version of Excel and then the standalone desktop version of Excel and how you can't use the analytical tool pack with the online version, but you can use it with the desktop version. In this video, we're gonna dive into data types, and it's really important that we do that. This is just, again, a review if you're already familiar with Excel. So definitely, if this is a review for you, review it, or just feel free to skip forward.

0:37However, it's really important that we cover this because again, this is available to beginners. So if you don't know about these data types, there may be some sort of confusion later down the road. And this will be pretty straightforward and it won't take very long. So let's dive into Excel data types. Okay, so here we have the desktop version of Excel, and what we're gonna do is take a look at each one of these data types. So here, we have player. So there's some sort of a game, right? So you have score_1, score_2, some results, the average of those scores, and then the date that this took place.

1:15Okay, so this took place in January of 2021. And let's take a look at this. Well, so what data type would this be? So there are multiple data types. So this would be considered a text data type. So go ahead and write in the data types below each one of these. And you wanna check your answer with the solutions, and we'll do that at the very end. So right here, we have... Let me write in all the different kinds of data types. So text, we have numbers, these can be integers, floats, or ones and zeros for Boolean values.

1:49So these are numbers. And then we have date and time, right? So these will be the same objects, same data type. And then we have logical. And then we have... We already talked about logical, and then there's dates and let's see what else. Yeah, we can also do error. Okay, so these are our dated types. So let's match them to the bottom here. So that's what we're doing in this video.

2:20So this is clearly text, right? And we know that because the only thing that's inside of this column is text. So it's good that we have the same data type. That's usually very helpful. For example, if you wanted to sum all of these and then you had a name in there, well, you couldn't add name with some numbers, so that's why you wanna have them to remain the same data type. Okay, so this one and this one, what do you think these are? Well, these are numbers. If I drag this little handle over, it'll give me the same value.

2:54So that's a nice little feature for dragging this handle down and up so that you repeat that value across multiple columns or rows. Okay, so we have text, numbers. And then what is this one right here? So let's go to the solutions and you can see that it says logical. So let's dive into that. So let's first type in logical and let's click on this. Whenever I do that, this value, you're gonna see it right here in this sort of formula window, what's the content of that formula.

3:29So this is logical. So the first one, double-click here, and then you see what's actually happening. So we're saying B2 here is greater than 50 and C2 is greater than 80, which these are two. That is not the case for either of these, so you get a FALSE. If these are both true, if this was 51 and this was 81, it's now TRUE.

4:02And that's why it's logical, because it's using this AND, which is a logical operator. We'll talk more about this, but there's gonna be IF, AND, or different kinds of logical operators. And this is a logical data type, so that's the takeaway here. Not necessarily what we're doing, even though that's pretty clear. You can see that the condition here, same thing, we're checking to see if these two scores, the first one is over 50 and if the second one is over 80.

4:33And we can go to a true one right here. So this one's over 60 and this one's over 80, and that's why it's TRUE. Okay, so this is the, again, the logical data type. Let's keep going. So here, we have an average, and this first one right here is an error. So let's go back to the solutions. So you can see clearly it's an error data type. And I'm referring to these. I'm not referring to the ones that are correct, just these data types right here. And those are called error data types, okay?

5:04And then let's talk about that. So here, what's the error? Well, first we're dividing, we're adding B and C scores, right? And then we're dividing them by two, I believe. Yeah, so that we can get an average and that is 34.525. Here, we were dividing this score by zero. So you're gonna get an error whenever you try to divide by zero. So that's a very common error and that's why it's an error data type.

5:34And we're again, just, we're really focusing on these errors right here. All of these worked fine and these are functions and we'll talk about those a little bit later. Or actually, these are formulas and we'll talk about functions a little bit later. Okay, and so this last one is pretty clear. This is a date/time object and that's pretty straightforward. Let's look at the solutions. And that's exactly what we have. We have text, numerical, logical, error, and date, okay? And let's go back to the start.

6:05And there's things that you can do with these. For example, here, if you wanted to add the sum, you could just say something like equal this one plus this one plus this one, and so on and so forth. We could keep doing this, C2, C3, C4. And what is that equal? 189. C2, C3, C4. And that's what these scores add. And that's why it's good to have these in that sort of data type. But you can also use functions so that you can just say something like SUM and then you can grab all of these scores up to there and then you get the sum of all of those.

6:42And that's why it's important that they're all the same data type. All right, so that's it for Excel data types. Again, just a review. In the next video, we're gonna actually start using these and start adding numbers together and working with different cells. And in doing so, you're gonna quickly find out that there's a limitation and there could be an easier way to do things, and that's when we jump into functions. So we'll check out formulas first and do things manually, and then we'll see why it's advantageous to use formulas. I hope this has been informative and I'd like to thank you for viewing.

0:07Welcome back. In the last video, we talked about Excel data types and in this video, we're gonna talk about formulas and how to use those data types to perform math operations. So we're gonna keep this focused on math operations and the reason for that is I think it's the easiest way to demonstrate the usefulness of using functions. When you do this manually, there's gonna be an easier version and that's what we're gonna lead into. And then in the next skill, we'll jump into functions. But for now, let's check out the Excel data types and use them to write our own formulas.

0:45Okay, so here we have addition, subtraction, division, multiplication, percentage, and exponentiation. So let's talk about each one. So how do we do 1 + 1? Well, if you just typed in 1 + 1 enter, nothing would happen. And the reason for that is that you need to add an equal sign. So that's what creates a formula. Once you have that formula, then you get an answer, right? And you don't have to use a parentheses either.

1:15You can and it'll still give you the same answer, but it's optional. But some people prefer that, especially if you're doing multiple operations and it might make sense to do that, it might be cleaner. And we will dive into parentheses when we're using functions again, but for right now, to do 1 + 1, this is how you would write it. It's = 1 + 1 with or without the parentheses. Then you get that answer. So how about trying this one? So how would you subtract 2 from 1?

1:47And again, this is why Excel is so great. It's pretty intuitive. So from what I've shown you already, you could see that it's basically like this and you'll get 1. And you don't have to use the parentheses. So how about 15 divided by 5? Equal sign and the division symbol is this slash and then you get 3. All right, so let's do multiplication. So multiplication isn't written like this. And let me actually be very clear about this.

2:20You don't write it like this. If you do that, we found a typo in your formula and we tried to correct it to. And look what it does. It actually changed it for us. And if we go back there and double click on it, you see that it changed it from that X to this asterisk. And that's the multiplication symbol. So that's the correct answer. 5 times 5 is 25. And percentage. What do we do here? Well if we do 0.5, then you get 0.5. And if you grab this and then you type, click on this percentage style, then you get 50%, right?

2:56So 50% is 0.5, it could be 0.50. And you can also change that from a number to a percentage. Okay, and so here we're gonna leave it as a percent. And exponentiation, this is how you would write it. With an equal sign first. And you use this caret, the up caret. And you get 4. So 2 times 2 is 4. And we could try this with different numbers. So let's take a look at the solution so far.

3:27Actually let's keep going and look at the solution at the very end. I think that's always the best practice anyway. Okay, so let's jump over here. So now we have these two sets of numbers , two column of numbers. So num a and num b. So let's do things to them. So here we'll be just adding our information into these cells, right? Like = 15 / 5 for 15 divided by 5. But that's not the most common way of using Excel. You would have some sort of existing values and then you would wanna perform some sort of operation on them.

3:58So here, let's go ahead and for every pair of these numbers, add them. So how would you do that? Try to give it a shot. I think it should be pretty intuitive. Okay, so let's say I'm here and I wanna add 2 plus 8. I would say equals. And I could do this and get the right number, but if I drag this down, I'm just gonna get the same information over and over and over. So that's not the best way to do that. So what you can do is grab this cell, right?

4:32So this is a cell reference. So we're referencing H2 plus I2. And if we hit enter, then we get 10. And here's what's really cool. So if you get this handle in this bottom right corner, the drag handle, the fill handle, and you pull it all the way down, it's gonna give you the appropriate cells. If you look here, you can see what's happening every time I click on one of the, let me escape and then click on these.

5:06And you can see that here. You can see the formulas are changing, right? And yeah, so that's very useful. So it'd be pretty easy to fill these out. So you only have to do the first one and then use the fill tool to just drag them down. So, what am I gonna do here? Well I'm gonna say equal sign H2 minus I2. And this time I just wrote it in, I didn't drag on it 'cause it's faster. And if you do that, you get negative six. That makes sense. And then drag it all the way down. And here you get all of those answers. All right.

5:38So try to do the rest of these yourself by pausing on the video before I do them, all right? So hopefully you got the division. So let's go ahead and do that. So it's equals H2. And then I2. Okay, so that's how you would do that. And then we get this fill handle and we do all of them. And then we get all of the division. So multiplication, let's do the same thing there. So we're gonna say H2 times I2, okay?

6:122 times 8 is 16. And we drag this down. 2 times 3 is 6. Or 3 times 2 is 6. So that looks correct. And percentage, what are we gonna do there? What's the percentage of these two? Okay, so first, what is 2 of, what percentage is 2 when you're thinking about 8, right? So 8 goes in here 4 times, it'd be 25%. So how do we do that? So here we're just gonna say H2 divided by I2, and then let's do that.

6:48And you get 0.25, right? And if you went here and you added the percentage sign, and we do that here, you'd get 25%. Okay? So then you could do that, just like that. Let me go back to General and leave that like that. Okay, so we have this and then we're gonna just say percent and add that and then go ahead and drag this all the way down. And so it's basically what we did here is the same as division, except that we did the division and we changed it into the percentage.

7:20So that's one way of doing that. There are multiple ways of doing that. All right, so last one is exponentiation. So what are we gonna do here? So equal H2 to the power of I2. Okay, 256. All right, and so let's just take our fill handle and drag it down and that's what we get. Okay, so let's go to solutions and here are your solutions. And if you have any questions, just check these out and be sure to review those and make sure that you're clear on the Excel data types and the formulas.

7:57Now, if we wanted to do this same thing, but with functions, right? For example, if you wanted the average. Let's say like you wanted the total here, you could actually add a total. The easiest way to do that would be a sum. And that's gonna be a sum function. And all you'd have to do is just grab this there to there and just say, that's my sum. And then you could actually say total. And that's how you would do that. And the same thing, you can grab this and just grab it over here and then now you see that by just dragging it over.

8:34Look, if you're looking over here, or if I double click in here, you could see that we're talking about the sum of H2 to H11. If I double click in this cell, we're talking about the sum of I2 to I11. And I did that just by dragging it to the right. And so we could continue that here. I could just drag these like this. This one doesn't have anything because there's no numbers here. But here this is the totals, right? So that's one way and that's what makes it so useful is that what we're doing here is you we're using a sum function.

9:10All right, so I think that's it for this video. I hope this has been informative and I'd like to thank you for viewing.

0:07Welcome back. In the last video we talked about formulas and how to perform math operations, and then at the very end we saw the the need for functions and how that could be really useful. So in this video, we're not gonna get into the formulas or the functions yet. That's gonna be in the next skill, the next group of videos for now, what we're gonna do is make sure that we have the analysis tool pack installed and take a quick look at the Titanic data set that I downloaded from Kaggle and then perform some quick exploratory data analysis on that.

0:40So to give you an idea, well, well first of how to install the analysis tool pack and how to use it as we're progress through this course, we'll use the analysis tool pack for statistical testing such as a T-test to perform an AA test and a B test. And then finally for hypothesis testing. Alright, so let's take a look at the analysis tool pack and how to install it and how to use it. Okay, so here we have, this is the Titanic data set. So when you download this, this is what you'll have.

1:13And so let's go ahead and install the tool pack. So to do that I'm gonna Mac and I think this should be pretty easy for, or the same instructions for a Windows operating system. Go to the data toolbar or the ribbon and then you click on analysis tools and then we're gonna click on analysis tool pack and click on, okay. Okay, so now we have data analysis here. So let's go ahead and grab passenger ID and then click on data analysis.

1:49Okay, so now we have some different options here. A lot of options, right? So what we're gonna do is use descriptive to statistics first, but lemme just show you that you can have a histogram T-test and this is what we're going to be using if T test for two sample, assuming unequal variances. That's what we're gonna use for an AA test and an AB test later. But you can also do regression, a Nova correlation testing and lots of, I mean this is pretty cool, so this makes it a lot easier to perform statistics.

2:23And what we're gonna do is jump into descriptive statistics. Okay, so here we have a label in the first row. Yes, it's gonna be from here, colon there. All right, and summary statistics. Okay. All right, there we go. So there is our statistics for our EDA for the passenger id.

2:53Let me click on these. So what I did was I just clicked on this in between section here to make them bigger. When they're a little squished like this, you can just double click here and that sets the width so that you can see everything. Okay, cool. So here's the passenger id and let's do one more. And again, if you wanted to do each one of these manually, you'd have to do basically formulas, right? So that's kind of cool. For example, min would be a formula min for minimum, max for maximum.

3:24Then the mean, would that be an average function? And so you'd have to do all of these individually. So right here you can already see that it's saving you a lot of time. So let's take a look at the age column and get some EDA there as well. Okay, so I'm just gonna click on age, then go to the data so that I have the data ribbon. Then go to data analysis, descriptive statistics. So labels in the first row. So I'm just gonna say F1 so that it knows that F1 is age.

3:58So that's the first row and we're gonna grab some summary statistics and make sure that's clicked. And this is gonna go to Q3, which is right here. So that looks about right. So let's go ahead and check that out. Okay, so let's go ahead and double click here on Q to make that a little bit bigger. And now we can see some information. So first the passenger ID is something that doesn't repeat and that's what you want in an id. So that's good. Now when you look at this, the mean will tell you that that what the average is, since that's not super helpful, but there's no mode, right?

4:29Because there's no repeated number and that's good. That's what we want to know. And the minimum is one and the maximum is 8 91. So that's how many records that we have. 891. When you look at the age, you can see some interesting information here. And again, these are all be functions. So I did all of this all at once. So a great time saver. And here's the average, the mean and the the median and the mode. And here we're getting, so we have the, the, the median and here's the average.

5:01It's a little bit higher here. So there's some skewing going on. And the count is what's interesting here that's really standing out for me while we have a a a hundred and something missing values. So there, there's quite a few missing values and we already explored that. They're just missing values here. I don't know exactly why that was. However, if we look at this again, we can look at the minimum and maximum age and we could see that, you know, there were some babies and the oldest person on the Titanic was 80.

5:31Okay, that's good to know. So this is really just giving us a lot of information very, very quickly and it really was just pretty easy to install. All we did is just went to the data analysis tool pack here and make sure this was clicked and clicked, okay. All right. And there are other things that we could do. I don't think we're gonna do those right now. Let me go ahead and make sure this is back to where it was at like one 60 or something. So for example, if I went to data analysis, I said that I wanted to do correlation testing, we could do that.

6:01We are also going to do t-test and you can even do a z test. And so what we're gonna do is later we're gonna perform a two sample T-test, assuming on equal variances. So there's a lot that you can do here. There's moving averages, histograms and we already, you did descriptive statistics, there's co correlation analysis of variance. Lots of good stuff here. Okay, so that's pretty much it for this video.

6:33Alright, so we've installed the analysis tool pack and you can see that it's a time saver in a lot of different ways, especially when we get into t-tests and things like that. For right now, we explored the Titanic data set and we did some quick exploratory data analysis using the analysis tool pack as again it was like 15 functions or something like that, but it just popped it out immediately and we're able to explore the, the IDs and compare those to the age and, and see that we had some missing records and, and again we're able to see the minimum and maximum age and the average age and see that it was skewed because we saw that the median was a little bit different than the the mean things like that.

7:12Okay, so that's it for this video. I hope this has been informative and I'd like to thank you for viewing.