Question

Consider the following Excel multiple regression of output of Total Sales on the (c) other (predictor) variables. Provide some important arguments about the fitted multiple regression model. (Give one argument about each of the three main outputs.) [4 marks] SUMMARY OUTPUT Regression Statistics Multiple R 0.9870 R Square Adjusted R Square 0.9741 0.9721 Standard Error 116.2766 Observations 43 ANOVA Significance F df SS MS F Regression 19817036.22 6605678.74 488.58 5.82876E-31 Residual 527289.46 39 13520.24 Total 42 20344325.68 P-value Coefficients Standard Error t Stat Intercept -2179.5191 9.58406E-07 375.2892 -5.8076 Qf ales 7.5751 0.3573 21.2016 5.17048E-23 QtrNumSales 0.3286 4.36582E-18 0.0215 15.3137 QtrMedDays 1.2209 0.3035 0.763093806 4.0223

Answer 1

Model is best fit since regression model has R square of .9741 and adjusted R squared is .9721 which tells that model is good fit. Which means most of the dependent variables is captured by independent variables.

F statistic is significant which means that it is rejecting null hypothesis.

P-value is significant for intercept, QtrMedSales, QtrNumSales but not for QtrMedDays because it has very large p value. Which also tells that QtrMedDays not has significant effect in the regression models.