The client is thinking of spending $32,500 in direct mail next week. What is your best estimate of what the following week’s sales will be at that level of spending?
Week | Sales | Direct Mail | Corrected |
1 | $121,230 | 9800 | 42047 |
2 | $212,090 | 21200 | 9800 |
3 | $99,980 | 561000 | 21200 |
4 | $429,780 | 41300 | 56100 |
5 | $496,370 | 26700 | 41300 |
6 | $316,450 | 32100 | 26700 |
7 | $286,980 | 52900 | 32100 |
8 | $496,110 | 73100 | 52900 |
9 | $389,080 | 69500 | 73100 |
10 | $787,350 | 54400 | 69500 |
11 | $446,310 | 8700 | 54400 |
12 | $389,410 | 29900 | 8700 |
13 | $420,040 | 24300 | 29900 |
14 | $629,380 | 42300 | 24300 |
15 | $419,370 | 82000 | 42300 |
16 | $740,070 | 60200 | 82000 |
17 | $498,730 | 48900 | 60200 |
18 | $621,780 | 27900 | 48900 |
19 | $317,620 | 37600 | 27900 |
20 | $427,270 | 68621 | 37600 |
using excel>data analysis>regression
we have
SUMMARY OUTPUT | ||||||
Regression Statistics | ||||||
Multiple R | 0.367221 | |||||
R Square | 0.134851 | |||||
Adjusted R Square | 0.086788 | |||||
Standard Error | 171962.5 | |||||
Observations | 20 | |||||
ANOVA | ||||||
df | SS | MS | F | Significance F | ||
Regression | 1 | 8.3E+10 | 8.3E+10 | 2.805675 | 0.111216 | |
Residual | 18 | 5.32E+11 | 2.96E+10 | |||
Total | 19 | 6.15E+11 | ||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
Intercept | 465778.1 | 44800.48 | 10.39672 | 4.89E-09 | 371655.8 | 559900.5 |
Direct Mail | -0.56117 | 0.335024 | -1.67501 | 0.111216 | -1.26503 | 0.142689 |
the regression equation is
Sales = 465778.1 -0.56117 * Direct Mail
for direct mail = 32,500
estimated sale = 465778.1 -0.56117*32500 = 447540.075
The client is thinking of spending $32,500 in direct mail next week. What is your best...
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