Estimation of linear regression model
A CEO of a large pharmaceutical company would like to conclude if he should be placing more money allotted in the budget next year for television advertising of a new drug marketed for controlling asthma. He wonders whether there is a strong relationship between the amount of money spent on television advertising for this new drug called XBC and the number of orders received. The manufacturing procedure of this drug is very difficult and requires stability so the CEO would prefer to generate a stable number of orders. The cost of advertising is always an important consideration in the phase I rollout of a new drug. Data that have been collected over the past 20 months indicate the amount of money spent of television advertising and the number of orders received.
The use of linear regression is a critical tool for a manager's decisionmaking ability. Carefully read the ex below and try to answer the problems in terms of the problem context. The results are as follows:
Month

Advertising Cost (thousands of dollars)

Number of Orders

1

$68.93

4,902,000

2

72.62

3,893,000

3

79.58

5,299,000

4

58.67

4,130,000

5

69.18

4,367,000

6

70.14

5,111,000

7

83.37

3,923,000

8

68.88

4,935,000

9

82.99

5,276,000

10

75.23

4,654,000

11

81.38

4,598,000

12

52.90

2,967,000

13

61.27

3,999,000

14

79.19

4,345,000

15

80.03

4,934,000

16

78.21

4,653,000

17

83.77

5,625,000

18

62.53

3,978,000

19

88.76

4,999,000

20

72.64

5,834,000

Assume there is a statistically significant relationship. Use the least square method to find the regression equation to predict the advertising costs based on the number of orders received. Please make use of the regression procedure within Excel under Tools > Data Analysis to construct this equation.