- [Instructor] Let's say we're looking
at some type of disease
and we want to see if there's any relationship
between people having antibodies for that disease
and whether they are adults, children or infants.
And if you don't know what antibodies are,
these are things that your immune system keeps around
so it's very easy to recognize future infection.
But you don't have to worry too much about that
for this video.
In this video, we're just trying to think about
how we can visualize data to understand
if there's a relationship between having antibodies
and the age of the individual.
So let's say we go out and collect a bunch of data.
So we test 120 adults
and 114 have antibodies, six don't.
We test 60 children,
54 have antibodies, six don't.
We test 20 infants, and then eight
have antibodies and 12 don't.
So we can just look at this data,
but this really still doesn't give us
a visual representation of what's going on.
One step we can take, what's still doesn't give us
a fully visual representation,
is to just think about percentages
that might help us think about the likelihood
of having antibodies.
So if we calculate the percentages,
we might see something like this.
For example, 114 over 120
is 95%, or 95% have antibodies.
That 114 over one 20 is 95%.
And then the number that don't have antibodies,
this six right over here,
that is 5%, six over 120.
And you can do that for each of the categories.
54 over 60 is 90%.
While six over 60,
you can do that math in your head, is 10%.
And we can do the same thing for the infants.
Eight out of 20 is 40%
while 12 out of 20 is 60%.
So that helps us a little bit.
It helps us think about,
well, what's the percentage of adults
that have the antibody or children or infants?
But if we really want to visualize it,
we can look at two different types of visualizations.
One we can call a segmented bar chart,
and I will show a segmented bar chart
for this data right over here.
Now in a segmented bar chart, we group,
we have a bar for each category here
and we're making adults, children and infants
the different categories because we're thinking
maybe that has something to do with the likelihood
of having antibodies.
And then for each bar, for example, this adult bar,
you can see the percentage that have the antibodies
and the percentage that don't.
So 95% of the adult bar is filled in blue.
That's for yes, they have the antibodies.
And 5% is filled in red.
And then for children,
you can see that 90% is filled in blue
and 10% is filled in red
because 10% don't have the antibodies.
And then for infants, you can see
that 40% is filled in blue
and 60% don't have the antibodies.
Now, this by itself is pretty useful
to visually see, alright, it looks like adults
are much more likely to have the antibodies
than children, and children are far more likely
to have the antibodies than infants.
And so it looks like this idea of making a bar
for each of adults, children or infants
was a good way to start to understand
the likelihood of having antibodies.
You could have done it other ways.
You could have had a bar for have antibodies
and another bar for not have antibodies.
And then you could have segmented the bar chart
by whether they are adults, children, or infants.
But if you did that,
that would have been trying to understand
whether having antibodies or not having antibodies
is predictive of whether you're an adult, child or infant
while this one makes, at least to me,
a little bit more sense that whether you're an adult,
child or infant might be predictive
of whether or not you have antibodies.
But there is some information lost
in this segmented bar chart.
For example, we have lost the fact
that we have sampled, or we have tested
a lot more adults than children
and far more children than infants.
So one way to incorporate that data
back into a visualization
to essentially show how many people
you sampled in each of these categories,
we can generate what's known as a mosaic plot.
So this is a mosaic plot right over here.
And one way to think about it is
we have just adjusted the width
of each of these bars
based on how many people we tested.
So we tested 200 people.
And so you can view this width right over here
as being 200.
And you can see that we tested 120 adults.
So the width of this first bar,
I guess you could say,
although now we're dealing with a mosaic plot,
this width right over here would be
60% of this entire width,
which you can see that it is.
And then the children are 60 of the 200 that we tested.
And so this width right over here
would be 60 over the entire 200,
or it would be about 30% of the entire width.
And we can see that we tested
the fewest number of infants.
And so this 20 right over here
represents the 20 infants we tested.
And the reason why this mosaic plot
conveys more information,
it conveys all the same information
that our segmented bar chart does.
But it also gives us a sense that we tested
more adults than children
and far more children than infants.
And it's also easy to then look at it and say, okay,
of the total number of people who don't have the antibodies,
so that would be the red area right over here,
even though we tested the fewest number of infants,
it looks like infants make up a large chunk
of the total number of folks
who don't have antibodies.
So I'll leave you there.
The whole point of this video is to just understand
why a segmented bar chart or a mosaic plot
will be useful in future videos.
We'll get more practice analyzing them.