Correlational Research: Definition, Purpose & Examples

Lesson Transcript
Instructor: Devin Kowalczyk

Devin has taught psychology and has a master's degree in clinical forensic psychology. He is working on his PhD.

This lesson explores, with the help of two examples, the basic idea of what a correlation is, the general purpose of using correlational research, and how a researcher might use it in a study. Updated: 11/27/2019

Definitions in Correlational Research

Your brain can do some really cool things. For instance, you learn that a particular jingle means the ice cream trucks are nearby. The louder the jingle, the closer it is. And if you were lucky enough to have several types of ice cream trucks, you will recognize which jingle goes with which ice cream truck.

The world is full of things where if thing A happens, then there is a good chance that thing B will happen. If thing A is the jingle, then there is a good chance that thing B, the ice cream truck, is close by. We can also make things more complicated by thing A being the loudness of the jingle and thing B being the distance to the ice cream truck. As the loudness increases, the distance shrinks. As the distance increases, the loudness goes down.

This is kind of a silly example, but it's an example of how you naturally correlate one event with another. A correlation is simply defined as a relationship between two variables. The whole purpose of using correlations in research is to figure out which variables are connected. I'm also going to start referring to the things as variables; it's a more scientific name. This simple definition is the basis of several statistical tests that result in a correlation coefficient, defined as a numerical representation of the strength and direction of a relationship.

Correlation research is looking for variables that seem to interact with each other, so that when you can see one changing, you have an idea of how the other will change. This often entails the researcher using variables that they can't control. For example, a researcher may be interested in studying the preference for ice cream based on age. If we cannot assign age, does that mean we have to scrap the whole correlation? Nope!

Since the researcher cannot assign certain variables, this would mean the researcher is performing a quasi-experimental study. A quasi-experimental study is defined as an experiment in which participants are not randomly assigned. There are different techniques for how we might overcome this, and I encourage you to explore this in other lessons.

While we focus on correlation in research, we must also note that the correlation can be positive or negative. Positive correlations mean that as variable A increases, so does variable B. A negative correlation is defined as when variable A increases, variable B will decrease. Please note that I did not say how much the other variable moves when the first variable changes.

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Coming up next: The Relationship Between Variables: Correlation Coefficient & Scatterplots

You're on a roll. Keep up the good work!

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  • 0:05 Definition
  • 3:00 Example 1
  • 4:22 Example 2
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Example 1

When looking for correlations, a researcher will look for patterns - what they have seen happen again and again. A simple pattern known to every teacher, but unfortunately not every student, is the link between studying and grades. The studious student who studies is more likely to score a higher score on their test. Students who don't study much are less likely to score as high as those who do.

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