Knick knacks Co. is evaluating store performance for retail distributors of their products. Management believes that the key factor in retail sales is square footage of display space devoted to the products. They have collected data from 132 stores and hired you to analyze these data, which include square footage of KnickKnack display space (in sq. ft), the size of the local population (in 10,000's, e.g., town of population 35,000 is represented in data as Population = 3.5), and whether the printed advertisements were circulated in local newspaper in each week (Ads = 1 if circulated, and if not circulated), and weekly sales of Knick knacks (in $1000's) (dependent variable). Residual plots do not exhibit any significant sign of violations on linear regression assumptions. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 4.708 132 ANOVA df SS MS F Significance F 206.8885 6.68E-49 - Regression Residual 3 128 13754.63 2836.621 16591.251 4584.877 22.1611 Total 131 Coefficients Standard Error Intercept 2.607 16.4084 Ads 0.586 0.1755 Space (sq. ft.) 2.331 1.2438 Population (10,000's) 1.100 0.2873 t Stat 0.1589 3.3362 1.8741 P-value 0.8758 0.0042 0.0632 0.0015 3.8278 What is the estimated regression line for the weekly sales given by the regression output? Sales = 0.586 +2.607 Ads +2.331 Space + 1.100 Population a. Sales = 2.607 + 0.586 Space + 2.331 Ads + 1.100 Population b. Sales + Be + B1 Space + B2 Ads + B3 Population + E OC. Sales = 2.607 + 0.586 Ads +2.331 Space + 1.100 Population