There are two basic types of variables that we come across in statistics.
The first type are known as qualitative variables and the second type are known as quantitative
variables.
A qualitative variable is used to describe something that is either categorical or non-numeric.
A good way to think about qualitative variables is first four letters of the word qual, standing
for quality.
By quality we're referring to the actual type of something as opposed to how many or an
exact numerical value.
Common qualitative variables can include things like:eye color, gender, religious affiliation,
political organizations that you affiliate with, and even your actual major.
The important thing, the commonality here with a qualitative variable, is that they
are non-numeric in nature.
They're not describing the amount of something, but rather they're describing a type of something
if you will.
For example, if we were to go ahead and survey students related to their major at a college
it would look something like this.
So really our focus here is on the non-numeric variable is finding out which particular major
they are.
Not necessarily the quantity within any particular major although we can certainly go there.
Now a quantitative variable works in a very similar fashion, with the exception of the
fact that with a quantitative variable what we're focusing on how much or how many of
something.
So some common examples of quantitative examples can include everything from company revenues
on an income statement, it can include the age of employees, it can include salary of
employees, it can even include things like IQ.
Now quantitative variables can fall into two specific categories.
They either fall into what we call discrete variables or continuous variables.
A discrete variable is one that can only assume a certain value.
And what happens are there are certain gaps that exist between these values.
A common example of a discrete variable would be the number of rooms in a house.
So if I were to ask you how many rooms there are in your home, you would have to give me
a discrete variable.
You would tell me something along the lines of maybe two, three, four, maybe even five
rooms.
And the reason that it's a discrete variable is because you're only allowed to select certain
options there.
You can't go between one and two, so say 1.25 or 1.75.
And that's the reason why it's a discrete variable because you can't select, there are
gaps between those values.
We can only select those figures, those one's, two's, three's, four's, and five's of course.
Now a continuous variable is one that can assume any value within a certain range.
So a common continuous variable would be profits.
So profits can be very very specific.
You're not only predisposed to certain selections.
There's not certain gaps.
So they can be very very detailed.
That would be an example of that.
You can also say that square footage in a house could be a continuous variable as well.
Although typically we do round those things since we don't want to be concerned with the
smaller details, but ultimately that would be a continuous variable.
Thank you for watching this video on the different type of statistical variables.
In our next video, we're going to focus on the different levels of measurement that we
see in statistics.
For questions please leave them in the comment box below, and I'll do my best to get back
to them in a timely fashion.
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Thanks for watching.