Answer:
The Salesperson age after performing each of the correlation and regression analyses in the prior questions shows that:
Even if a correlation is substantial, you don't know for sure until you measure it in a regression model with several other relevant variables.
Step-by-step explanation:
The simple difference between correlation and causation is that a correlation measures the linear relationship between two variables, while causation is a statistical measure that establishes that one event or variable is the cause of another event or variable. With correlation established, one needs to study the strength of the relationship through a regression analysis before concluding on how one variable affects another variable.