Yummy Lunch Restaurant needs to decide the most profitable location for their business expansion. Marketing manager plans to use a multiple regression model to achieve their target. His model considers yearly revenue as the dependent variable. He found that number of people within 2KM (People), Mean household income(income), no of competitors and price as explanatory variables of company yearly revenue.

The following is the descriptive statistics and regression output from Excel.

1. Complete the missing entries from A to L in this output
2. Derive the regression model
3. What does the standard error of estimate tell you about the model?

d. Assess the independent variables significance at 5% level (develop hypothesis if necessary in the analysis)?

Revenue People Income Competitors Price 41522.96 2.8 5.68 0.142857 0.051030203 343965.68 5307.89863 345166.5 #N/A 5970.26 139.0845281 6032 5917 582.1376385 41339.5 Mean Standard Error Median Mode Standard Deviation Sample Variance Sum 3 5.75 #N/A 3 6 37532.51115 983.47613 1.010153 1.020408 0.360838027 0.130204082 1408689393 967225.2984 4116.334718 16944211.51 2076148 50 298513 140 284 17198284 50 Count 50 50 50 # SUMMARY OUTPUT Regression Statistics Multiple R 0.77 R Square A Adjusted R Square B Standard Error 25139.79 Observations 50.00 | ANOVA Significance F df SS MS F H 3.0831E-08 Regression Residual D 40585376295 28440403984 F G Total E 69025780279 Coefficients Standard Error t Stat P-value -68363.1524 6.4394 78524.7251 3.7051 -0.8706 1 0.3886 0.0891 Intercept People Income Competitors Price 7.2723 0.9358 J 0.0000 -6709.4320 3818.5426 K 0.0857 15968.7648 10219.0263 L 0.1251