A large mail-order house believes that there is an association between the weight of the mail it receives and the number of orders to be filled. It would like to investigate the relationship, in order to be able to predict the number of orders based on the weight of the mail. From an operational perspective, knowledge of the number of orders will help in the planning of the order-fulillment process. A sample of 25 mail shipments is selected within a range of 200 to 700 pounds. The results were given in the file mail.xlsx attached below mailxlsx a. Assuming ear relationship, use the least-squares method to determine the regression coefficients bo and b1 o The dependent variable is (fill in the blank by orders or weight) (X is independent variable) Standard deviation of independent variable Sx Standard deviation of dependent variable Sy- o Correlation coefficient r= Slope b1 intercept b0 b. Predict the average number of orders when the weight of the mail is 500 pounds. (i.e. X-600) Y QUESTION 2 n problem 1, the weight of mail was used to predict the number of orders received (3DP) a Determine the coefficient of determination r-squared b. Find the standard error of the estimate SyX c. How useful do you think this regression model is for predicting the number of orders received? Your answer is (3DP) (fill in the blank by useful or not useful)