Charting Our Data: Part 2

We've got our ten minute intervals, 0:00 now we just need to know how many runners belong to each one. 0:02 To do this, we're going to use the count if's function again. 0:05 But first, 0:09 we'll need to copy the range of finishing times to get it on the clipboard. 0:10 I'll click in here, pick the range of finishing times and use Cmd or Ctrl+C. 0:15 Then, let's start in this first cell, by typing =countifs. 0:21 And then, let's paste in the range of finishing times. 0:28 Next for the first criteria, let's make sure the finishing time is 0:31 greater than 120 minutes by adding a greater than sign in quotes. 0:36 And then concatenating that with the cell that contains 120 by using an ampersand. 0:43 So ampersand and then we want to click on the 120 over here. 0:48 Now, to finish out the interval, 0:53 we just need to make sure that their time is also less than a 130. 0:55 Let's copy our first two parameters and 1:00 paste them at the end, after adding a comma. 1:04 Then let's change the greater than sign to 1:08 a less than sign and change A16 to A17. 1:12 Then let's hit Enter, and we've got 0. 1:16 Not quite what we were expecting. 1:21 It turns out that in Google Sheets, when you see a duration like this, 1:24 behind the scenes, the units they're using are days. 1:29 So, if we want our comparisons to work, we'll need to convert our minutes to days. 1:33 To convert minutes to days, since there's 60 minutes in an hour, and 1:39 24 hours in a day, you would just divide the minutes by 60, and then 24. 1:43 Back in our equation, let's divide both A16 and 1:49 A17 by 60, and then 24. 1:54 And now it looks like we've got 2 people who finished after 2 hours, 2:03 but before 2 hours and 10 minutes. 2:08 That's more like it. 2:11 Now let's drag this formula down to the bottom to get our data. 2:13 And now that we've got all of our data, let's make a chart. 2:21 Let's put our cursor in the upper left cell, right here on finishing interval and 2:25 then while holding down Ctrl+Shift for Windows or Cmd+Shift for Mac, 2:30 hit the right arrow, and then the down arrow to select all of our data. 2:35 Then let's click on the chart icon to create the chart. 2:40 Here we finally get to see what our data looks like. 2:45 But before we get to that, there's one thing I'd like to clean up. 2:49 This chart has a legend that takes out most of the right side of the chart, 2:53 leaving us with a lot of empty space for 2:58 some information that we already have on the left. 3:01 To remove the legend inside the Chart editor, let's click on the Customize tab. 3:04 Then click on the Legend drop down and for the position let's set it to None. 3:11 Now let's close the Chart Editor and 3:18 move our chart to the top of the sheet next to the summary data. 3:20 So what do you think? 3:36 Does it look like a bell to you? 3:37 While our data is mostly normally distributed, 3:40 it does seem to have a slight skew to it. 3:42 But would you say it's a negative skew, or a positive skew? 3:45 One way to find out would be to use the skew function. 3:49 Just for fun, in any one of these cells down here, let's call the skew function 3:53 and pass in the range of finishing times. 4:00 And since that's greater than 0, it looks like we've got a positive skew. 4:11 Visualizing your data is a great way to gain insight into what's going on 4:17 without having to do a lot of work. 4:22 In the next stage we'll dive deeper into our data and 4:24 look at how typical data analysis task breaks down. 4:27