SUMMARY OUTPUT | ||||||||
Regression Statistics | ||||||||
Multiple R | 0.993709623 | |||||||
R Square | 0.987458816 | |||||||
Adjusted R Square | 0.987378251 | |||||||
Standard Error | 514.2440271 | |||||||
Observations | 471 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 3 | 9723795745 | 3241265248 | 12256.7707 | 0 | |||
Residual | 467 | 123496711.4 | 264446.9194 | |||||
Total | 470 | 9847292456 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | -267.1127974 | 42.01832073 | -6.357055513 | 4.8988E-10 | -349.68118 | -184.54441 | -349.68118 | -184.54441 |
Fuel cost (000,000) | 0.449917223 | 0.098292092 | 4.577349137 | 6.0451E-06 | 0.25676768 | 0.64306676 | 0.25676768 | 0.64306676 |
Salary (000,000) | -0.327915884 | 0.188252958 | -1.741889678 | 0.08218614 | -0.6978436 | 0.04201186 | -0.6978436 | 0.04201186 |
Average seat miles (000,000) | 0.140064895 | 0.004458029 | 31.41857134 | 2.942E-117 | 0.13130462 | 0.14882517 | 0.13130462 | 0.14882517 |
write the equation line for all observation and interpret the result in terms of the positive/negative influence of factors on revenue.
Regression Equation
Therefore,
Revenue is impacted positively by fuel cost and average seat miles i.e. when fuel cost/ average seat miles increase, revenue also increases. Revenue is impacted negatively by the salary. When salary increases, revenue reduces.
Statistical significance
The p-value for the intercept, the coefficient of fuel cost, and the coefficient of average seat miles are less than 0.05. So, their values are statistically significant at 95% confidence level. The same is not true for the coefficient of salary because the p-value is more than 0.05.
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