Defining correlational research

The purpose of correlational research is to examine the relationship between two or more variables to determine if they are associated.

This method allows us to determine if two factors vary together, but it cannot tell us if one causes the other.

For example, researchers might be interested in whether watching aggressive content on television is associated with increased aggressive behavior.

To study this, they would measure the number of hours of aggressive television watched by a group of children and also their degree of aggressive behavior.

The Correlation Coefficient

The strength and direction of the relationship between two variables is represented by a mathematical statistic known as a correlation.

This coefficient can range from a positive value of plus one to a negative value of minus one, indicating different types of association.

A positive correlation indicates that as the value of one variable increases, we can predict that the value of the other will also increase.

In In contrast, a negative correlation tells us that as the value of one of the variables increases, the value of the other decreases.

An example of a positive correlation would be that more hours of studying leads to higher grades on tests taken.

An example of a negative correlation could be that more hours of studying leads to fewer hours spent partying.

The Big Caveat: Correlation Does Not Imply Causality

The inability of correlational research to demonstrate cause-and-effect relationships is its most crucial drawback, and one that we must remember.

The simple fact that two variables are correlated does not in any way mean that one of the variables is the cause of the other.

Following the previous example, we cannot say that watching aggression on television causes aggressive behavior in children.

It is equally possible that children who are already aggressive by nature will choose to watch television programs that have more violent content.

The Problem of The Th