The Difference between Correlation and Causation

Causation always implies correlation, but correlation does not imply causation. But why?

Correlation simply implies a relationship between variables, but does not indicate that the covariation exists due to a direct or causal link between them. Conversely, causation goes beyond implying a relationship; it implies a specific type of relationship known as a causal relationship (or cause-and-effect relationship). For a causal relationship to exist between two variables, one must influence the other; when one variable changes, it must bring about a change in the other. The variables, therefore, have a causal link. 

Reflecting back on the initial statement; variables that have a causal relationship are related and, therefore, causation always implies correlation. However, as variables can be related without directly influencing each other, correlation does not imply causation.

Let’s understand a few reasons as to why we cannot imply causation even if we identify correlation:

• Third/Confounding Variable Issue: Sometimes, the two variables being studied are related due to a third variable. In such cases, the third variable influences both the other variables separately, indicating that the variables being studied do not have a cause-and-effect relationship.
• Directionality Issues: In certain cases where variables do have a causal relationship, there are directionality issues. This means that it is hard to decipher which variable is ‘the cause’ (also known as the independent variable) and which is ‘the effect’ (also known as the dependent variable). In such situations, where the causal relationship cannot be proven, we cannot imply causation. 
• Chain Reaction: There may be multiple different variables influencing the correlation between the two variables being studied. This chain reaction indicates that the variables do not have a cause-and-effect relationship but are simply correlated to one another.