Question

What is the difference between correlation and causation?

Answer 1

Correlation is an association between two variables, while causation implies a cause-and-effect relationship. Correlation does not necessarily imply causation because there may be other factors, called confounding variables, that are responsible for the observed correlation.

Step-by-step explanation:

Correlation and causation are two concepts in statistics that are often misunderstood. Correlation refers to the association between two variables, where a change in one variable is associated with a change in the other variable. Causation, on the other hand, implies a cause-and-effect relationship between two variables, where changes in one variable directly cause changes in the other variable.

It's important to note that correlation does not necessarily imply causation. Just because two variables are correlated, it doesn't mean that one variable causes the other. There could be other factors, called confounding variables, that are responsible for the observed correlation.

For example, let's consider a correlation between ice cream sales and crime rate. These two variables may be positively correlated, meaning that as ice cream sales increase, so does the crime rate. However, the causation here is not direct. The true cause of the correlation could be the temperature, with hotter weather leading to both increased ice cream sales and increased crime rate. In this case, temperature acts as a confounding variable.

Answer 2

correlation between variable mean that change in one variable is the cause of the change in the values of the other variable. Causation indicates that one event is the result of the occurrence of the other event; i.e. there is a causal relationship between the two events