If computing a causal linear regression model of Y = a + bX and the resultant r² is very near zero, then one would be able to conclude that A)Y = a + bX is a good forecasting method. B)Y = a + bX is not a good forecasting method. C)a multiple linear regression model is a good forecasting method for the data. D)a multiple linear regression model is not a good forecasting method for the data.

Question

Quizplus · Accepted Answer

A correlation coefficient (r) close to zero indicates that there is little or no linear relationship between X and Y. Therefore, Y = a + bX is not a good forecasting method since there is no significant relationship between the two variables. A and C can be ruled out since the question only asks about the validity of the given linear regression model and not about other models. D cannot be concluded based on the given information.

If Computing a Causal Linear Regression Model of Y =