Advertisement ($'000)	Sales ($'000)
657.00	1750.00
1155.80	4309.21
1342.29	5079.37
1365.57	5176.80
1166.09	4348.55
1036.18	3906.69
1277.76	5200.00
1540.52	5823.67
1545.02	5837.48
1181.91	4410.17
1592.26	5500.00
1041.20	4300.00
1150.95	4290.89
1180.93	4406.31
1326.06	5010.77
1140.09	4250.41
1467.33	5576.78
872.30	3546.34
1591.22	5969.30
1430.67	5438.95
1371.25	5279.98
1382.51	5334.59
1393.76	5389.20
1405.02	5443.81
1416.28	5498.42

A. Construct a scatter plot with this data.

B. Do you observe a relationship between both variables?

C. Use Excel to fit a linear trend line to the data. What is the fitted regression model?

D. What is the slope? What does the slope tell us? Is the slope significant?

E. What is the intercept? Is it meaningful?

F. What is the value of the regression correlation coefficient, r? What does r tell us?

G. What is the value of the coefficient of determination, R²? What does R² tell us about explained variation in y?

H. Use the model to predict sales when the business spends $885 ($'000) in the advertisement. Does the model underestimate or overestimate sales?