An analyst ran a regression for the last 60 months with the monthly returns for Procter and Gamble (PG) as the dependent variable and th monthly returns for the S&P 500 Index as the independent variable. The results are: Regression Statistics Multiple R 0.521185 R Square 0.271634 Adjusted R Squa 0.259076 Standard Error 0.04096 Observations 60 ANOVA Regression Residual Total Intercept X Variable 1 df SS MS F gnificance F 1 0.03629 0.03629 21.63032 1.96E-05 58 0.097309 0.001678 59 0.133599 Coefficientsandard Err t Stat P-value Lower 95% Upper 95%ower 95.0%pper 95.09 0.003808 0.005288 0.72008 0.474368 -0.00678 0.014393 -0.00678 0.014393 0.451966 0.097179 4.650841 1.96E-05 0.25744 0:646492 0.25744 0.646492 Based on this analysis, the systematic variance of PG stock is 0.52 0.27 0.04 0.26 0.45 None of the above

7) Below is a multiple regression in which the dependent variable is market value of houses and the independent variables are the age of the house and square footage of the house. The regression was estimated for 42 houses. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total df 2 39 41 0.745495 0.555762 0.532981 7211.848 42 SS 2537650171 2028419591 4566069762 Coefficients Standard Error MS 1.27E+09 52010759 F 24.39544 Significance F 1.3443E-07 Upper 95% t Stat P-value Lower 95% Intercept 47331.38 13884.34664 3.408974 0.001528 19247.6673 House Age -825.161 607.3128421 -1.35871 0.182046 -2053.5662 Square Feet 40.91107 6.696523994 6.109299 3.65E-07 27.3660835 7A. What is the estimated regression equation for determining the market value of houses? 7B. Discuss tests of significance of the regression 7C. What percentage of the variation in the dependent variable, Market Value, is explained by the regression…

Suppose that a regression line is found to be ý = 0.5470x +7.7000 What is the predicted value for a = 7? O a. 11.53 O b. 54-45 C. 53-35 O d. -3.87

An economist is interested to see how consumption for an economy (in $ billions) is influenced by gross domestic product ($ billions) and aggregate price (consumer price index). The Minitab output of this regression is reproduced below. Coefficients Term Constant GDP Price Model Summary S 0.299 Error Total Coef Analysis of Variance Source Regression -0.0861 0.7654 -0.0006 R-sq 0.98% DF • 2 7 9 SE Coef 0.5644 0.0574 0.0028 R-sq(adj) 0.98% Adj SS 33.4163 0.6277 34.0440 T-Value O a. 7 O b. 9 O c. 10 O d. Cannot be determined from the information given. -0.1520 13.3400 -0.1290 Adj MS 16.7082 0.0897 P-Value 0.8837 0.0001 0.8330 F-Value P-Value 186.325 0.049 Referring to the table above, how many observations were there in this study?