7. The Accucorp Company has the data below on the number of customers for 15 weeks and the weekly sales (in thousands of dollars). Below is a scatterplot of the data for each of the 11 semesters James attended college in Indiana (4 spring, 4 fall, 3 summer). The temperatures displayed are the average temperature of the semester (in degrees Fahrenheit). Here is the data and its scatterplot. Sales vs Customers 14 '3' 12 o .._ D a 10 C o a 3 y=0.0308x-15.032 g ' R==0.6574 f, 6 .E w 4 U) I.) E 2 o 780 800 820 840 860 880 900 920 940 960 Weekly Customers The regression equation and r2 are displayed on the graph above. a) Which is the likely explanatory variable? Which is the likely response variable? b) What is the slope of the regression line? What does it mean in terms of the story? c) Describe the strength and direction of the relationship between customers and sales. (I) Suppose the number of customers for a week is 870. Predict the weekly sales. Is this a valid prediction? e) Suppose the number of customers for a week is 690. Predict the weekly sales. Is this a valid prediction? f) Calculate the residual for the week with 855 customers. g) What is the correlation coefficient between the number of customers and the weekly sales? Is this correlation strong, weak, or moderate? h) It the number of customers in a week were to increase from 800 to 900, what is the predicted change in sales? i) What percent in the variation in weekly sales is NOT explained by the linear relationship with the number of customers