Why is it important that the relationship between the explanatory and response variable be linear when performing a linear regression analysis?

A- A linear relationship implies a strong relationship exists between the two variables which is critical when performing a linear regression analysis.

B- A linear regression analysis relies on a straight line being fit between the points on a scatter plot.

C- A non linear relationship implies that the correlation coefficient is 0 which implies no relationship exist between the explanatory and response variables.

D- A non linear relationship indicates that the explanatory variable is not helpful in predicting the response variable.