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In this video we'll use our 10 minute intervals to finish creating our chart!
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
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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.
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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.
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.
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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.
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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.
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
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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.
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,
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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.
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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.
3:20
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.
3:42
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.
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
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look at how typical data
analysis task breaks down.
4:27
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