In: Statistics and Probability
A sales manager for an advertising agency believes there is a relationship between the number of contacts and the amount of the sales. To verify this belief, the following data was collected: For each sales contact a particular person makes, the amount of sales is expected to: Select one: a. Decrease by 2.195 thousand units b. Increase by 2.195 thousand units c. Decrease by 12.201 thousand units d. Increase by 12.201 thousand units
Data is not given but i have taken as bellow,
Here we have to do regression analysis. Independent variable (X) : Number of contacts
Dependent variable: Sales (Y)
Following is the output of regression analysis generated by excel:
SUMMARY OUTPUT | ||||||
Regression Statistics | ||||||
Multiple R | 0.975362147 | |||||
R Square | 0.951331317 | |||||
Adjusted R Square | 0.945247731 | |||||
Standard Error | 9.31044574 | |||||
Observations | 10 | |||||
ANOVA | ||||||
df | SS | MS | F | Significance F | ||
Regression | 1 | 13555.4248 | 13555.4248 | 156.3767508 | 1.56492E-06 | |
Residual | 8 | 693.475199 | 86.68439987 | |||
Total | 9 | 14248.9 | ||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
Intercept | -12.20103752 | 6.559575958 | -1.86003449 | 0.099925317 | -27.32744679 | 2.92537175 |
Number Of Contacts | 2.194641842 | 0.175500178 | 12.50506901 | 1.56492E-06 | 1.789937705 | 2.599345979 |
Slope of least sqaure regression line:
Slope: 2.195
Intercept: -12.201
Since slope is positive so for each unit increase in independent variable, dependent variable increased by 2.195 units. Hence, option b is correct.