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In this video we'll use our 10 minute intervals to finish creating our chart!

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We've got our ten minute intervals,

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now we just need to know how many runners belong to each one.

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To do this, we're going to use the count if's function again.

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But first,

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we'll need to copy the range of finishing times to get it on the clipboard.

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I'll click in here, pick the range of finishing times and use Cmd or Ctrl+C.

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Then, let's start in this first cell, by typing =countifs.

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And then, let's paste in the range of finishing times.

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Next for the first criteria, let's make sure the finishing time is

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greater than 120 minutes by adding a greater than sign in quotes.

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And then concatenating that with the cell that contains 120 by using an ampersand.

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So ampersand and then we want to click on the 120 over here.

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Now, to finish out the interval,

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we just need to make sure that their time is also less than a 130.

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Let's copy our first two parameters and

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paste them at the end, after adding a comma.

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Then let's change the greater than sign to

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a less than sign and change A16 to A17.

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Then let's hit Enter, and we've got 0.

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Not quite what we were expecting.

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It turns out that in Google Sheets, when you see a duration like this,

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behind the scenes, the units they're using are days.

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So, if we want our comparisons to work, we'll need to convert our minutes to days.

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To convert minutes to days, since there's 60 minutes in an hour, and

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24 hours in a day, you would just divide the minutes by 60, and then 24.

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Back in our equation, let's divide both A16 and

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A17 by 60, and then 24.

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And now it looks like we've got 2 people who finished after 2 hours,

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but before 2 hours and 10 minutes.

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That's more like it.

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Now let's drag this formula down to the bottom to get our data.

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And now that we've got all of our data, let's make a chart.

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Let's put our cursor in the upper left cell, right here on finishing interval and

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then while holding down Ctrl+Shift for Windows or Cmd+Shift for Mac,

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hit the right arrow, and then the down arrow to select all of our data.

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Then let's click on the chart icon to create the chart.

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Here we finally get to see what our data looks like.

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But before we get to that, there's one thing I'd like to clean up.

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This chart has a legend that takes out most of the right side of the chart,

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leaving us with a lot of empty space for

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some information that we already have on the left.

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To remove the legend inside the Chart editor, let's click on the Customize tab.

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Then click on the Legend drop down and for the position let's set it to None.

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Now let's close the Chart Editor and

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move our chart to the top of the sheet next to the summary data.

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So what do you think?

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Does it look like a bell to you?

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While our data is mostly normally distributed,

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it does seem to have a slight skew to it.

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But would you say it's a negative skew, or a positive skew?

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One way to find out would be to use the skew function.

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Just for fun, in any one of these cells down here, let's call the skew function

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and pass in the range of finishing times.

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And since that's greater than 0, it looks like we've got a positive skew.

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Visualizing your data is a great way to gain insight into what's going on

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without having to do a lot of work.

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In the next stage we'll dive deeper into our data and

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look at how typical data analysis task breaks down.
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