Sales and Advertising Expenditures for a Sample of Seven Travel Agencies
|
Firm |
Sales |
Advertising |
|
A |
15000 |
2000 |
|
B |
30000 |
2000 |
|
C |
30000 |
5000 |
|
D |
25000 |
3000 |
|
E |
55000 |
9000 |
|
F |
45000 |
8000 |
|
G |
60000 |
7000 |
Using Excel, generate a regression output and discuss the results, the interpretation of the output and statistical properties of a model.
| SUMMARY OUTPUT | |||||||||
| Regression Statistics | |||||||||
| Multiple R | 0.874781011 | ||||||||
| R Square | 0.765241817 | ||||||||
| Adjusted R Square | 0.718290181 | ||||||||
| Standard Error | 8782.643763 | ||||||||
| Observations | 7 | ||||||||
| ANOVA | |||||||||
| df | SS | MS | F | Significance F | |||||
| Regression | 1 | 1257182986 | 1.26E+09 | 16.29851 | 0.009950761 | ||||
| Residual | 5 | 385674157.3 | 77134831 | ||||||
| Total | 6 | 1642857143 | |||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | ||
| Intercept | 11573.03371 | 7150.826978 | 1.618419 | 0.166497 | -6808.752226 | 29954.81964 | -6808.752226 | 29954.81964 | |
| Advertising | 4.971910112 | 1.231542173 | 4.037142 | 0.009951 | 1.806130173 | 8.137690051 | 1.806130173 | 8.137690051 | |
| Regression equation: | |||||||||
| * Sales = 11573.033 + 4.972*(Advertising) | |||||||||
| * The regression result shows that the sales is positively related to advertising. An increase | |||||||||
| in the advertising by $1 will lead to increase in sales by $4.97. | |||||||||
| * The R2 = 0.76 shows that the independent variable advertising explains 76% of the | |||||||||
| variation in dependent variable sales.. | |||||||||
| * The t-statistic associated with variables sales is greater than 3 shows that the sales | |||||||||
| variable is statistically significant. | |||||||||
Get Answers For Free
Most questions answered within 1 hours.