A correlational study determines whether or not two variables are correlated. This means to study whether an increase or decrease in one variable corresponds to an increase or decrease in the other variable.
It is very important to note that correlation doesn't imply causation. We'll come back to this later.
There are three types of correlations that are identified:
A correlation coefficient is usually used during a correlational study. It varies between +1 and -1. A value close to +1 indicates a strong positive correlation while a value close to -1 indicates strong negative correlation. A value near zero shows that the variables are uncorrelated.
It is very important to remember that correlation doesn't imply causation and there is no way to determine or prove causation from a correlational study. This is a common mistake made by people in almost all spheres of life.
For example, a US politician speaking out against free lunches to poor kids at school argues -“You show me the school that has the highest free and reduced lunch, and I'll show you the worst test scores, folks” (nymag.com). This is a correlation he is speaking about - one cannot imply causation. The obvious explanation for this is a common cause of poverty: people who are too poor to feed their children will not have the best test scores.
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