Part (a) Interpret the estimated value of the slope coefficient, i.e., explain w

Question

Part (a)           

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) For an unit increase in sales, we can expect an increase of 0.0626 units in the response variable

b) If the sales is 0, the response variable will have a value of 4.1807

c) Note: The response variable is not mentioned.

Assuming it is the profit, it does not make sense as there cannot be any profit when the sales is 0.

Please try to find a reasoning on your own using the example above.

d) Yes it is significant as the p-value corresponding to sales is very close to 0 , in other words less than 0.05(significance level)

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