SUMMARY OUTPUT Regression Statistics Multiple R 0.996583913 R Square 0.993 Adjusted R Square 0.992 Standard Error 17.64924228 Observations 27 ANOVA df SS MS F Significance F Regression 5 952538.941 190507.7882 611.590323 0.000 Residual 21 6541.410811 311.4957529 Total 26 959080.3519 Coefficients Standard Error Intercept SQFT INVENTORY ADVERTISING FAMILIES STORES -18.8594 16.2016 0.1746 11.5263 13.5803 -5.3110 t Stat 30.15022856 -0.625514572 3.544437472 4.570985577 0.057606068 3.031541426 2.532103272 4.552052832 1.770456651 7.670514089 1.705426574 -3.114160352 P-value Lower 95% Upper 95% 0.538 -81.56024003 43.84142542 0.0002 8.830511324 23.5726338 0.0063 0.054836805 0.29443356 0.0002 6.260470849 16.79206489 0.0000 9.898446522 17.26217885 0.0052 -8.857600533 -1.76434311 Multivariate Regression: Which collection of factors affect sales in our franchises and how? Can we create a model to design a store given certain demographics so we can achieve a certain level of sales? Examine each of the variables and see if any variables need to be transformed to improve the multi-variate model.