Welcome to Highline BI 348 class video number 26.
And if you want to download this workbook BI 348 chapter
2 start or the finished file, click on the link
below the video.
In this video, we're going to briefly talk
about a box and whisker plot.
Now, back in our prerequisite class Business 210,
we created this chart, and it's simply
a way of displaying the spread, or dispersion, or variation
in the data in a visual way.
Now, this is score data.
In a box plot with whiskers, the box part is the inside part.
The first line represents quartile one,
the second line is the median, and the third line
is quartile three.
Now, sometimes the mean is listed too here,
and we can see the mean is below the median,
so we know there's a few small values pulling the mean down.
And then we have these whiskers that stretch out
to the smallest and the biggest value inside our outlier line.
Now, outliers require that we calculate
first the interquartile range.
If this is quartile one, and this is quartile three,
the interquartile range is simply
the difference between quartile three and quartile one,
and that range represents the inner 50% range of our data.
Now, we take that distance and we multiply it by 1.5.
Now, there are other multiples that you
can use-- for example, 2.2-- but the one
that our author uses is 1.5.
And actually, the one that Excel uses in its box and whisker
plot in Excel 2016 is 1.5 also.
So the idea to get to these lines, which mark anything
past these, or outliers, is to take interquartile range
times 1.5 And you subtract that from quartile one like this.
Now, if you get to 0, then you just take 0, right?
And for quartile three, here's quartile three,
you take the interquartile range and you multiply it by 1.5,
and that's the distance.
Now, prior to Excel 2016, there is no way to do this in Excel
except for with about a 30-step process,
and I do have videos at YouTube of how to do that.
Now, in this class BI 348, we have
XLMiner in our lab, which you can use to create a box plot.
I do not have a camera connected to those computers,
so I can't show you how to use XLMiner.
But I am going to show you the amazing new Excel 2016 box
and whisker.
Now, I just got Excel 2016.
Here are some scores for CPA, and I have two different data
sets.
This one actually lists all the score from CPA test 1.
Here's all the scores, CPA test 2, 3, 4, and 5.
This data set is a proper data set.
There's the header for CPA test 1, 2, 3, 4, 5,
and here are the scores.
Watch this.
I'm going to click on a single cell,
go up to Insert, and Charts, and look at this.
Not only do we have our box and whisker,
but there's a built-in histogram and Pareto chart.
So I'm going to go ahead and click this,
and you've got to be kidding me-- that is amazing.
Now, I'm going to click this, because this is chartjunk.
And there we have it-- five box and whisker plots.
We can compare the different tests,
and the different scores, and their distribution.
For each of them, we can see quartile one, quartile three,
and the median.
The x represents the mean.
The whisker for each one of them, and even our outliers.
Some of the things we can see here-- we can clearly
see for test number 5 the interquartile range, which
represents the inner 50% the values, much higher
than any of the other data sets.
This one looks like it has the biggest spread
for that interquartile range.
Some other things we can notice.
Notice that the x, which represents the mean,
it's further down from the median
than any of these others.
And, of course, it has more outliers also.
It looks like all of the means are below except for this one,
and sure enough, we can see that there's
an outlier pulling this up.
We can also see an estimation for the range, right?
This one has the smallest range.
It looks like test 4 and test 1 have the biggest range.
Lots of things we can see in our box and whisker plot.
All right, so that is our last video for chapter 2.
Next week, we'll get busy learning
how to clean and transform data to prepare it for our analysis,
and in particular, we'll be looking at Power Query.
All right, we'll see you next video.