When doing research, variables come in many types. In this lesson, we'll explore the three most common types of variables: continuous, discrete, and categorical.
Imagine that you are a psychologist and that you want to do a study on whether tall people are smarter. You decide to gather a bunch of people together and get their IQs and height. If tall people really are smarter, you think, the taller the person is, the higher his IQ will be.
Measurement is the process whereby a feature is evaluated. Those features can be things like height or weight, or they could be more psychological in nature, like intelligence or anxiety levels.
In any given study, you are trying to measure (or evaluate) certain elements that change value depending on certain factors. These are called variables. Think of the word 'vary,' which means 'to change,' and you'll be able to remember variable.
Some variables change from person to person. For example, height is a variable because it changes from person to person; if everyone in the world was the same exact height, it wouldn't be a variable. Likewise, IQ varies from person to person, so it is another variable.
Other variables change across time. For example, a person's level of anxiety might change depending on the situation or the point in their life or for another reason. A person's age can be a variable, too: if you measure someone today and then a month from now, their age has changed.
There are three main types of variables: continuous, discrete, and categorical. Let's look closer at each one.
Okay, so you want to do a study to see if taller people are smarter. One of the first things that has to be done when designing a study is to identify your variables. In our study above, height and IQ are the variables that we are measuring.
Let's say that we want to measure height in inches. Some people might be 62 inches, and one or two might be 82 inches. And then, there are a bunch of people in between those two heights.
A continuous variable is one that can take any value between two numbers.
For example, between 62 and 82 inches, there are a lot of possibilities: one participant might be 64.03891 inches tall, and another person might be 72.67025 inches tall. And, there are literally millions of other possible heights between 62 and 82 inches.
So, how do you know if you've got a continuous variable? In general, a continuous variable is one that is measured, not counted. Height, for example, is measured. Weight is measured. Temperature, time, distance - all are continuous variables.
Let's say for a moment that instead of height, you want to measure how many siblings a person has and see if people with more siblings have higher IQs. The number of siblings a person has is a discrete variable, or a variable that has only certain values. For example, a person isn't going to have 2.34978 siblings; he will have two siblings or three siblings.
Remember how we said that continuous variables are measured but not counted? Well, discrete variables are counted. The number of times heads comes up when you toss a coin, number of students present in class, number of times a person has attended therapy sessions - these are all discrete variables.
To help see the difference between continuous and discrete variables, imagine a really tall mountain with a trail leading up to the top. Because the view is so wonderful, lots of people want to go to the top of the mountain, but not everyone is in shape enough to hike to the top, so they install an elevator with three stops: the bottom of the mountain, halfway up the mountain, and at the mountain's peak.
Now people have two options: they can take the trail or the elevator. The trail is like a continuous variable: a person on the trail can stop at any point between the bottom and the top. But, the elevator has just three possible places to stop. It is discrete because there are only certain values (or places) that it can stop.
So, we know that continuous variables can take on any value and that discrete variables only have certain values. But, what if our variable doesn't come in number form?
Let's go once more to our study on IQ, but now let's say that we want to compare gender and IQ to see if girls are smarter than boys. Gender is a categorical variable, or a variable that involves two or more non-numeric groups. Gender is categorical because people are either male or female. Marital status is another categorical variable: a person can be married, single, divorced, widowed, and so on. Hair color, major, political affiliation, how depressed a person feels - all of these are categorical variables.
Note that categorical variables are non-numeric. That is, when they are measured, they do not have a number. Sometimes, a researcher might assign a number to a categorical variable, but that number does not tell us anything about the variable. For example, we might decide to code gender in our study so that all the males get the number 0 and all the females get the number 1. What does that mean? It doesn't tell us anything about males or females, just that a person is a member of that group.
A variable is something that changes values. In research, examining variables is a major part of a study. There are three main types of variables: continuous variables can take any numerical value and are measured; discrete variables can only take certain numerical values and are counted; and categorical variables involve non-numeric groups or categories.
Your completion of this lesson could result in your ability to:
- Note the changeability of variables
- Discern the differences between continuous and discrete variables and provide examples of each
- Assess the unique characteristic of categorical variables