SCENARIO 3 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel to analyze the last 4 years of quarterly data (i.e., n = 16) with the following results: Regression Statistics Multiple R 0.802 R Square 0.643 Adjusted R Square 0.618 Standard Error SYX0.9224 Observations 16 ANOVA df SS MS F Sig.F Regression 21.497 21.497 25.27 0.000 Error 14 11.912 0.851 Total 15 33.409 Predictor Coef StdError t Stat P-value Intercept 3.962 1.440 2.75 0.016 Industry 0.040451 0.008048 5.03 0.000 Durbin-Watson Statistic 1.5911. Referring to Scenario 3, the value of the quantity that the least squares regression line minimizes is (KEYWORDS: least squares, properties, sum of squares) 12. Referring to Scenario 3, the estimates of the Y-intercept and slope are and respectively. (KEYWORDS: intercept, slope, estimation) 13. Referring to Scenario 3, the prediction for a quarter in which X - 120 is Y = (KEYWORDS: prediction of individual values) 14. The coefficient of determination (r) tells you A. that the coefficient of correlation (r) is larger than 1. B. whether r has any significance. C. that you should not partition the total variation, D. the proportion of total variation that is explained. 15. The standard error of the estimate is a measure of A. total variation of the Y variable. B. the variation around the sample regression line. C. explained variation. D. the variation of the X variable