Question

Discuss the relationship between covariance and causation.   Specifically discuss if covariance means causation. Why/ Why not? Provide an example.

Answer 1

A correlation is a measure or degree of relationship between two variables. A set of data can be positively correlated, negatively correlated or not correlated at all. As one set of values increases the other set tends to increase then it is called a positive correlation.

A causal relation between two events exists if the occurrence of the first causes the other. The first event is called the cause and the second event is called the effect. A correlation between two variables does not imply causation. On the other hand, if there is a causal relationship between two variables, they must be correlated.

Example - My mother-in-law recently complained to me: “Whenever I try to text message, my phone freezes.” A quick look at her smartphone confirmed my suspicion: she had five game apps open at the same time plus Facebook and YouTube. The act of trying to send a text message wasn’t causing the freeze, the lack of RAM was. But she immediately connected it with the last action she was doing before the freeze.

A study shows that there is a negative correlation between a student's anxiety before a test and the student's score on the test. But we cannot say that the anxiety causes a lower score on the test; there could be other reasons—the student may not have studied well, for example. So the correlation here does not imply causation.