|
1
|
3,500,000
|
12,600,000
|
|
2
|
7,200,000
|
15,500,000
|
|
3
|
3,100,000
|
10,800,000
|
|
4
|
1,600,000
|
8,700,000
|
|
5
|
8,900,000
|
20,300,000
|
|
6
|
5,700,000
|
21,900,000
|
|
7
|
6,300,000
|
25,600,000
|
|
8
|
9,100,000
|
14,300,000
|
|
9
|
10,200,000
|
15,100,000
|
|
10
|
7,300,000
|
18,700,000
|
|
11
|
2,500,000
|
9,600,000
|
|
12
|
4,600,000
|
12,700,000
|
|
13
|
8,100,000
|
16,300,000
|
|
14
|
2,500,000
|
8,100,000
|
|
14
|
3,000,000
|
7,500,000
|
|
16
|
4,800,000
|
12,400,000
|
|
17
|
10,200,000
|
17,300,000
|
|
18
|
5,100,000
|
11,200,000
|
|
19
|
11,300,000
|
18,500,000
|
|
20
|
10,400,000
|
16,700,000
|
a) Based on these data, does it appear that the strength of the relationship between sales and promotional expenditure is sufficient to warrant using linear regression forecasting model? Explain your answer
b) If the company's promotional expenditure is found to be K19,000,000 what would be the estimated annual unit sales? Explain.