In: Economics
Quantity of Automobile Lube Jobs # Q P # Cars Adv Pr 1 86 30 22.0 500 20 2 87 35 23.0 550 29 3 93 28 23.4 430 31 4 92 25 23.0 400 35 5 86 30 23.6 500 29 6 93 20 24.0 400 30 7 88 29 24.1 300 35 8 89 31 24.5 450 28 9 88 35 25.0 430 25 10 93 29 25.6 500 30 11 87 35 26.0 400 29 12 89 40 26.0 570 31 13 88 47 26.7 520 35 14 82 34 27.3 300 29 15 93 35 28.0 450 35 1. Run the data through Excel Regression - print output (10%)
SUMMARY OUTPUT | ||||||||
Regression Statistics | ||||||||
Multiple R | 0.807426944 | |||||||
R Square | 0.65193827 | |||||||
Adjusted R Square | 0.512713578 | |||||||
Standard Error | 2.292032224 | |||||||
Observations | 15 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 4 | 98.39921619 | 24.59980405 | 4.68263395 | 0.021760031 | |||
Residual | 10 | 52.53411715 | 5.253411715 | |||||
Total | 14 | 150.9333333 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | 63.47704203 | 11.60067182 | 5.471841892 | 0.00027235 | 37.62913444 | 89.32494961 | 37.62913444 | 89.32494961 |
P | -0.476873378 | 0.144258693 | -3.305682081 | 0.007936973 | -0.798301777 | -0.155444978 | -0.798301777 | -0.155444978 |
#Cars | 0.648949159 | 0.507981673 | 1.277505062 | 0.230284986 | -0.482904543 | 1.78080286 | -0.482904543 | 1.78080286 |
Adv | 0.027216626 | 0.00955891 | 2.847252186 | 0.017331545 | 0.005918048 | 0.048515204 | 0.005918048 | 0.048515204 |
Pr | 0.417481016 | 0.165243412 | 2.526460883 | 0.030052673 | 0.04929575 | 0.785666281 | 0.04929575 | 0.785666281 |
By taking Q as Y(dependent variable for no of jobs) we run the regression by making others independent variables.
To run regression, go to Data> Data Analysis> Regression.
Input the X and Y variables and click OK to obtain results.