Simple Regression
2.  A CEO of a large plastics manufacturing company would like to determine if she should be placing more money allotted in the budget next year for television advertising of a new baby bottle marketed for controlling reflux and reducing gas. She wonders whether there is a strong relationship between the amount of money spent on television advertising for this new baby bottle called Gentle Bottle and the number of orders received. The manufacturing process of this baby bottle is very difficult and requires advanced quality control 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 roll-out of a new baby bottle. 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 decision-making ability. Please carefully read the example below and try to answer the questions in terms of the problem context. The results are as follows:
Month
Advertising Cost
Number of Orders
1
$77,430.00
2,902,000
2
62,620
3,800,000
3
69,580
3,299,000
4
50,670
2,430,000
5
69,180
3,367,000
6
73,140
4,011,000
7
83,370
4,888,000
8
78,880
4,935,000
9
64,990
5,555,000
10
77,230
4,654,000
11
61,380
5,598,000
12
62,900
2,967,000
13
63,270
2,899,000
14
89,190
4,245,000
15
60,030
4,934,000
16
79,210
3,853,000
17
65,770
5,625,000
18
84,530
5,778,000
19
79,760
5,999,000
20
82,640
6,834,000
 a. Set up a scatter diagram and calculate the associated correlation coefficient. Discuss how strong you think the relationship is between the amount of money spent on television advertising and the number of orders received. Please use the Correlation procedures within Excel under Tools > Data Analysis. The Scatterplot can more easily be generated using the Chart procedure.
NOTE: If you…