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Lots of things end up being normally distributed. Are Boston Marathon results one of them?
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Let's try and find out if our data is
normally distributed by seeing how many
0:00
finishers finished within one, two, and
three standard deviations of the mean.
0:04
But first, we'll need to know
how many finishers there were.
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Let's add a row at the very top
by right clicking on row 1 and
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choosing insert 1 above.
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Then let's add a label for number of
finishers and make sure it's bold.
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Then in cell B1, let's type =COUNT,
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paste in our range of overall
finish times, and hit Enter.
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And there we go, 26,410 total finishers.
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Getting back to our standard deviations,
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let's add three labels below
our standard deviation label,
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and call them % in 1, % in 2, and % in 3.
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And let's leave them unbolded so
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they look like they belong with
standard deviation, because they do.
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Now, for % in 1, we need to find out
haw many runners finished within 1
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standard deviation of the mean.
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To accomplish this, we're going to use the
COUNTIFS function, which lets us give some
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criteria and then only returns the count
of values that match our criteria.
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We're going to count only runners that
finished within 1 standard deviation.
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And then divide that by the total
number of runners to get a percentage.
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Over in cell B11, let's type =COUNTIFS and
hit Enter to select it.
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Then let's paste in the range of
finishing times and add a comma.
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The next parameter is
the conditional statement.
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And it's entered as a string.
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So let's add two quotation marks and in
the middle, let's add a greater than sign.
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To find out if a runner is within 1
standard deviation of the mean, we need to
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check that their finishing time is greater
than the mean minus 1 standard deviation.
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Unfortunately, this data exists in a cell.
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So instead of typing the data in,
we should reference the cell directly.
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To do this,
we need to combine our greater than sign
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with our cell data by using an ampersand
to concatenate the strings.
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Let's add an ampersand after
the last quotation mark.
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Then let's select the average,
type a minus sign and
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then select the standard deviation.
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We're now counting all runners greater
than 1 standard deviation below the mean.
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So to finish up counting all the runners
within 1 standard deviation, we just need
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to add a criteria that they finished under
1 standard deviation above the mean,
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as well.
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To do this, let's just copy the range and
criteria that we just entered,
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add a comma, and then paste them back in.
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Finally, we just need to change this
greater than sign to a less than sign,
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and change this minus to a plus.
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And add a closing parentheses.
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For our last step, to turn this into
a percentage we just need to divide it by
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the total number of finishers.
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Which gives us about 69.47%,
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which is pretty close to the 68
of a normal distribution.
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And to make it look like a percent, we can
click up here and then choose percent.
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From here, we can find our other standard
deviation percentages pretty easily.
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But first, let's use F4 to make all
the references in this formula absolute.
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This way, when we drag the cell down,
it'll keep the same references.
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Then let's drag the cell down twice.
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And to get the % in 2 and 3,
inside the formula for those cells,
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we just need to multiply the standard
deviation by 2 or 3 respectively.
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And the standard deviation for
me is this teal-colored B10.
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So for % in 2, we'll multiply this by 2.
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And over here we'll multiply it by 2.
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And for % in 3 we'll do the same thing,
except with 3.
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All right, we've got 69.48,
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94.91, and then 99.76%.
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Remember, a normal distribution should be
about 68% within 1 standard deviation,
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95% within 2, and 99.7% within 3.
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So it looks like the finishing times
of runners in the Boston Marathon
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are pretty close to normally distributed.
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Coming up in the next video,
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we'll talk about the many different
flavors of data visualization.
5:10
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