Question

Define correlation, define causality, and explain the difference between the two

Answer 1

The statistical measure that describes the size and direction of a relationship between two or more variables , is called Correlation. Correlation between variables does not specify that change in one variable causes changes in the other variable.

Causality describes that one event is the result of the occurrence of the other event. This means the cause and effect relationship between two events are clarified.

Correlation describes only a direction of the relationship between two or more variables. Here we can not be assured that one variable change is the cause for the change of another variable. It just tells that as one variable changes , other variable also changes. There are three types of correlation.

Positive correlation: as one variable increase , the other variable also increases.

Negative correlation: one variable increases, other variable decreases.

No correlation: no relation found between two variables.

Eg: As a student's study time increases, so does his test average.

Here its only relation between student’s study time and test average.

This does not mean that increased study timings will cause increased test average. Some students need just a few hours to prepare for a test, while others need a few days. So we cannot make a cause and effect relationship here. This sentence just correlates two variables. As one increases, the other variable also increases. This is an example of positive correlation.

Causality explains how one variable or change in variable cause the change in the other variable. The cause and effect is clear here.

Eg: Smoking causes lung cancer. Here the variable smoking have a cause effect on the variable lung cancer. This is causality or causation. This clearly explains what causes the other variable or what changes the other variable. It has been scientifically proven that people who are smokers have high chances of getting lung cancer, while non smokers have minute chances for the same.