A marketing effectiveness analyst based in an emerging market obtains the following multiple linear regression output for predicting sales as function of price (Price), distribution (Distribution) and advertising (Ads). Some issues occurred with the software, and some of the regression results are corrupted on the output:

A B C D E SUMMARY OUTPUT Regression Statistics 4 R Square 0.80878129 5 Adjusted R Square 6 Standard Error 10.9283916 7 Observations 18 8 9 ANOVA 10 of SS MS F Significance F 11 Regression 3 7071.983598 2357.32787 19.7381976 12 Residual 14 1672,016402 119.429743 13 Total 17 8744 14 cor 15 Coefficients Standard Error t Stat P-value 16 Intercept 78.9692224 19.50842966 4.04795382 17 Ads 0.0138079 0.004364469 3.16370691 0.03181617 18 Price 1.091474972 -2.7111804 0.04935162 19 Distribution 0.28846343 0.143362263 0.02310069 20 21 mdu What interpretation should be made from the output? A. The coefficient for the price has a positive sign xar B. The t-stat for distribution variable is approximately 2.0 C. The adjusted R square is between 0.81 and 1.00 D. Intercept is not statistically significant at 0.05 level