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The following data were collected during a 14 month from a company’s sales reports. The report shows for each month, how much the company has spent for advertising (x) and how much sales were made during that month (y). Both the advertising and sales dollars are in units of $million. The Chief Executive Officer of the company is interested in the impact of the advertising spending on the actual sales.
Month | x | y | month | x | y |
1 | 24 | 79 | 8 | 23 | 83 |
2 | 32 | 85 | 9 | 19 | 75 |
3 | 45 | 89 | 10 | 20 | 77 |
4 | 42 | 86 | 11 | 17 | 90 |
5 | 56 | 101 | 12 | 29 | 93 |
6 | 52 | 100 | 13 | 38 | 95 |
7 | 35 | 88 | 14 | 26 | 90 |
(a) Provide the scatter plot for the data with the trend line.
(b) Obtain a linear regression line for the data. (Hint: You need to calculate a and b to get the linear
regression equation: y= a + bx)
(c) Predict the sales figures in months 15 and 16 if the advertising budgets allocated for months 15
and 16 are $25 million and $30 million, respectively.
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