Answer:
Kindly check explanation
Step-by-step explanation:
Given the data:
Sales(y) __Radio (x1) __ Newspaper (x2)
973 0 40
1119 0 40
875 25 25
625 25 25
910 30 30
971 30 30
931 35 35
1177 35 35
882 40 25
982 40 25
1628 45 45
1577 45 45
1044 50 0
914 50 0
1329 55 25
1330 55 25
1405 60 30
1436 60 30
1521 65 35
1741 65 35
1866 70 40
1717 70 40
The multiple regression equation obtained for the data:
With sales, y = predicted variable
Radio, x1 = predictor variable 1
Newspaper, x2 = predictor variable 2
ŷ = 13.10812X1 + 17.07885X2 + 149.19284
Slope b1, = for every unit change in Number of radio advert, there is a 13.10812 change in sales
Slope B2, = for every unit change in Number of newspaper advert, there is a 17.07885 change in sales
b0 = intercept = 149.19284, represents the estimated amount of sales if there was no sales reported from both radio and newspaper advert.
Sales where, X1 = $20,000; X2 = $20,000
ŷ = 13.10812(20000) + 17.07885(20000) + 149.19284
y = 603888.59284
Sales (y) = $603889
