In: Statistics and Probability
In its continuing study of the 3-For-All subscription solicitation process, a marketing department team wants to test the effects of two types of structured sales presentations (personal formal and personal informal) and the number of hours spent on telemarketing on the number of new subscriptions. The staff has recorded these data for the past 24 weeks in AMS14. Analyze these data and develop a multiple regression model to predict the number of new subscriptions for a week, based on the number of hours spent on telemarketing and the sales presentation type. Write a report, giving detailed findings concerning the regression model used. (Using Excel PHSTAT)
Week | New Subscription | Hours | Presentation |
1 |
1256 | 282 | Formal |
2 | 1405 | 336 | Formal |
3 | 1104 | 232 | Formal |
4 | 1333 | 321 | Informal |
5 | 975 | 261 | Informal |
6 | 769 | 212 | Formal |
7 | 585 | 162 | Formal |
8 | 923 | 266 | Informal |
9 | 1118 | 269 | Formal |
10 | 567 | 185 | Informal |
11 | 808 | 191 | Formal |
12 | 1005 | 226 | Formal |
13 | 1366 | 331 | Informal |
14 | 1180 | 311 | Informal |
15 | 851 | 222 | Formal |
16 | 848 | 227 | Informal |
17 | 1033 | 257 | Formal |
18 | 666 | 193 | Formal |
19 | 1289 | 325 | Formal |
20 | 840 | 216 | Informal |
21 | 995 | 251 | Formal |
22 | 1437 | 345 | Informal |
23 | 1133 | 286 | Informal |
24 | 1228 | 263 | Formal |
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.959782095
R Square 0.921181669
Adjusted R Square 0.913675162
Standard Error 74.89636127
Observations 24
ANOVA
df SS MS F Significance F
Regression 2 1376761.736 688380.8682 122.7177417 2.59768E-12
Residual 21 117798.7636 5609.464931
Total 23 1494560.5
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept -277.0200768 89.06006307 -3.110485971 0.005293533 -462.2306169 -91.8095366 -462.2306169 -91.8095366
Hours 4.864387329 0.312306521 15.57568289 5.19292E-13 4.214910365 5.513864293 4.214910365 5.513864293
Presentation' 96.37228728 32.4439516 2.97042384 0.007298234 28.90139636 163.8431782 28.90139636 163.8431782
1) So the equation of the regression is
New subscriptions = -277.02 + 4.86*Hours + 96.37*Presentation
Presentation = 1 if Formal otherwise 0
2) Coefficient of determination R^2 = 92.11%. So 92.11% of the variation in the dependent variable is explained by the variation in Hours and Presentation.
3) The formal presentation has 96.37 subscriptions more when the presentation is informal.
4) For every one hour increase, new subscriptions also increase by 4.86