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Continuous, Discrete & Categorical Variables: Definition and Examples

Continuous, Discrete & Categorical Variables: Definition and Examples
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  • 0:05 Variables
  • 1:42 Continuous
  • 2:57 Discrete
  • 4:29 Categorical
  • 5:51 Lesson Summary
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Lesson Transcript
Instructor: Natalie Boyd

Natalie is a teacher and holds an MA in English Education and is in progress on her PhD in psychology.

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.

Variables

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.

Continuous

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.

Discrete

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.

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