Part A: Using the summary output below: Interpret the estimated value of the int
ID: 3364139 • Letter: P
Question
Part A: Using the summary output below: Interpret the estimated value of the intercept, i.e., explain what the number means in this regression.
Part B: Does the estimated value of the intercept make sense? Why or why not?
SUMMARY OUTPUT
Regression Statistics:
Multiple R= 0.726492486
R Square= 0.527791332
Adjusted R Square= 0.526571154
Standard Error= 1444.608669
Observations= 389
ANOVA
Regession: df= 1 SS= 902692213.7 MS= 902692213.7 F= 432.5529349 Significance F= 4.90343E-65
Residual: df= 387 SS= 807628057.7 MS= 2086894.206
Total: df= 388 SS= 1710320271
Intercept: Coefficients= 4.180742184 Standard Error= 83.62471914 t Stat= 0.049994095 P-value= 0.960152886 Lower 95%= -160.2348801 Upper 95%= 168.5963645
Sales: Coefficients= 0.062578367 Standard Error= 0.003008878 t Stat= 20.79790698 P-value= 4.90343E-65 Lower 95%= 0.056662574 Upper 95%= 0.068494161
Explanation / Answer
Part A: Using the summary output below: Interpret the estimated value of the intercept, i.e., explain what the number means in this regression.
Answer : Here intercept value = 4.180742184
Here this number means in regression that if there is no sales (sales = 0) in the department then what is the revenue Here.
Part B: Does the estimated value of the intercept make sense? Why or why not?
Answer : NO, this estimated value of intercept doesn't make any sense as its value is very small and as we can see that p- value for the intercept is 0.96 which tells that this intercept doesn't makeanysense here. The given regression equation is straight line equation of y= mx nature. As revenue is directly proportions to sales so there is no need of intercept here.