Interpret the estimated value of the slope coefficient, i.e., explain what the n

Question

Interpret the estimated value of the slope coefficient, i.e., explain what the number means in this regression.

Part (b)   

Interpret the estimated value of the intercept, i.e., explain what the number means in this regression.

Part (c)   

Does the estimated value of the intercept make sense? Why or why not?

Part (d)   

Is the estimate of the slope coefficient statistically significant? Please answer “yes” or “no” and explain how you can tell.

SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.726492486 0.527791332 0.526571154 1444.608669 389 ANOVA MS Sianiticance F Regression Residual Total 1 902692213.7 902692213.7 432.5529349 4.90343E-65 387 807628057.72086894.206 388 1710320271 P-value Coefficients Standard Errort Stat 4.18074218483.624719140.049994095 0.960152886 -160.2348801 168.5963645 0.062578367 0.003008878 20.79790698 4.90343E-65 0.056662574 0.068494161 Lower 95% Upper 95% Intercept Sales

Explanation / Answer

a) slope coefficient = 0.062578637

This tells us if sales increase by 1 unit, the dependent variable (y) increases by 0.062578637 unit.

b) Intercept = 4.18

Intercept tells us that if sales = 0, then dependent variable is 4.18

c) The data doesn't mention what dependent variable is. Cant really tell if intercept is right or not.

Suppose dependent variable is Demand, then if sales = 0, demand = 4.18

So, it can be right

d) Slope coefficient p value = very small < 0.05

So, null is rejected and thus we can say Yes slope coefficient statistically significant

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