Final answer:
A spurious correlation is an apparent causal relationship between two variables which is actually due to one or more other variables. It occurs when two variables are correlated but not causally related.
Step-by-step explanation:
In statistics, a spurious correlation is an apparent causal relationship between two variables which is actually due to one or more other variables. It occurs when two variables are correlated but not causally related.
For example, let's say there is a positive correlation between ice cream sales and crime rate. However, this correlation is not because eating ice cream causes crime or vice versa. The confounding variable in this case is temperature, as both ice cream sales and crime rate increase during hot summer months. Therefore, it is important to consider other factors and potential confounding variables when interpreting correlations.
In conclusion, a spurious correlation is a statistical illusion of causality between two variables that is actually explained by other factors.