 Statistics and Excel bell curve. People wait example part number one. Get ready, taking a deep breath, holding it in for 10 seconds, looking forward to a smooth, soothing Excel. Here we are in Excel. If you don't have access to this workbook, that's okay because we'll basically build this from a blank worksheet. But if you do have access, three tabs down below. Example, practice blank. Example, in essence, answer key, practice tab, having pre-formatted cells so you could get to the heart of the practice problem. The blank tab, blank worksheet with just our practice data so we can practice formatting the cells within Excel as we work through the practice problem. If you don't have access to practice data, you could use resources such as Kaggle.com. You can also try to create your own data to practice with by going to the data tab up top, the analysis group and the data analysis tool that we saw in a prior presentation. If you don't have this analysis group, then you can go into the options and possibly add it as we saw in a prior presentation as well. Back to the home tab, down to the example tab to get an idea of what we will be doing. Our data is going to be related to weights of people. We also have heights if you want to practice with that as well, but we're focused on the weights this time measured in pounds. Now this will be similar to what we've seen in the past. There's two or a couple major differences however. One is going to be that we have a whole lot more data of weights and weights as you would imagine you would think that because it's something that's related to nature, people's weights, that it would follow a bell shape type of distribution. The more data that we have, the more likely that the actual example, if it conforms to a bell shape distribution, will stimulate a bell shape distribution. So that's one thing. We have a lot more data in this example than prior examples. We're also going to be building our graph over here and we're going to use a similar technique but slightly different in the technique to get this between column that we will then use to build our graph, trying to come up with some strategies that you might be able to build your graphs fairly quickly so that you can use them when you're working these practice problems. And we'll do a little bit more with the Z score calculations and formulas as well. All right, let's go to the blank tab and get started. I'm going to remove the Kaggle thing. I'm going to select the entire worksheet this time and format the data before we get started, selecting the triangle, right clicking on the worksheet, formatting the cells. I'm going to go to currency because I'm an accountant. That's where I like to go. I'm going to say negative numbers are bracketed and red and I'll keep the decimals for now. Let's go two decimals but no dollar signs. These are not dollars we're talking about. Now, if I say okay, obviously it trimmed up our data over here to just show the two decimals even though it had more than two decimals, right? Now, what I'm going to do is we could just hide the heights. I want to keep the heights there just because you might want to use those in practice in a similar method. You can do basically the same sample problem we're doing here but with the height stated if you want, but I don't need it right now. I'm going to go ahead and select columns. Let's first put a table around it and then I'll hide them possibly. Let's go up top, make this bold, home tab, font group, bold it and then I'll put my cursor somewhere in this group of numbers and go to the insert tab, tables group. I'm going to add a table to it. The dancing ants are doing their table creation dance. Looks kind of like a rain dance. It's hard to tell but you know it's different because obviously how would how would Excel know what to do if they did the same dance for everything? You know, spending his home tab, alignment, wrapping the text and I'm going to double click in here and just put some space so I can wrap the text with the spaces. Alright, and then I could just hide columns A and B because I'm not using those I'm going to put my cursor on a go over to be right click and hide them just hide it. Now note that if I was I was going to sort this data somehow possibly I had some blank cells in here where we didn't get the weights or we have some very high or low weights that don't look correct or something like that, then I might want to filter out those outliers that might not be correct depending on what I'm doing. If I was to do that, I would want my data on a separate tab because once I start filtering things, it'll collapse the rows. So but here I'm not going to do that. So I'm just going to keep my data on the same tab here and we'll do our normal calculation. So I'm going to make a skinny D skinny D. And then we're going to say sounds like a rapper's name or something skinny D skinny D's up, throwing down the base beat and doing some licks over it or something. Anyway, here's the mean equals the average tab. We're going to select our data. Now there's a lot of data. I'm going to select the data boom. And it's going to just pick up that entire table. If I go control shift down on this data, we're at 25,000 data points. So we have a lot more data control backspace. And then I'm going to say, All right, let's do the standard D. I'm just going to call it SD for the standard D. I'm going to say this equals ST. This is the population. So I'm going to pick up the population STD EV for the pop and the population, not your dad, the population, the pop. That's what I call it the pop. And then we're going to say, Okay, and then the median, the median, the one in the middle, hit the one in the middle, we're going to say the median tab, picking that up. Boom. And then the mode might not always be as applicable if you didn't have a whole lot of data because that shows multiple if multiple items are being hit and because we're using fractions of pounds, then it would be less likely. But since we have a whole lot of data, the mode will probably be applicable here too. Let's say the mode single mode just one please. I don't need like a whole bunch of modes. Boom. And okay, so now I can see that the mean is pretty close to the median, which is an indication that this group of data follows somewhat closely to the bell curve. And the mode is also there. Remember, the mode's kind of kind of tricky. Because if you didn't have a whole lot of data, the mode, that might not even have a mode because you have percent because you have these fractions of the measuring in this case of pounds, which means that you might not have a lot of duplicates. Whereas if you rounded them to a pound, it's more likely that the mode is going to be more applicable. But again, we have so much data right now that the mode will work. So now I'm going to say, All right, I'm going to graph this thing out. And so I'm going to make a bell curve because it looks like a bell curve would work. Before I do that, let's actually graph. Let's look at this data in terms of a histogram. If I select the entire thing, I'll just select the data. I just select the data. Then I'm going to go into the insert and then charts and just make a histogram say what does this thing look like from a histogram standpoint where we have the groups on the bottom and then and then how many and this is the buckets, the buckets on the bottom and how many of these numbers which there's a whole lot of them fall into each bucket. Now the point here is that this time we came up with something that looks a lot more like a bell curve than some of our prior examples due to the fact that we have a whole lot of data.