SUMMARY OUTPUT Regression Statistics Multiple R 0.59002 R Square 0.34812 Adjusted R Square 0.27569 Standard Error 1.67876 Observations 11 ANOVA of SS MS Feignificance F Regression 1 13.5451 13.5451 4.80625 0.05604 Residual 9 25.364 2.81822 Total 10 38.9091 Coefficient:andard Err t Stat P-value Lower 95%Upper 95%ower 95.09pper 95.0% Intercept 11.992 24.1428 0.49671 0.6313 -42.6229 66.6069 -42.6229 66.6069 X - Men 0.772 0.35214 2.19232 0.05604 -0.02459 1.56859 -0.02459 1.56859 RESIDUAL OUTPUT Observation cted Y - We Residuals dard Residuals 1 66.032 -0.032 -0.02009 N 64.488 -0.488 -0.30642 3 62.944 -0.944 -0.59274 4 66.804 -0.804 -0.50483 5 63.716 1.284 0.80622 6 64.488 2.512 1.57729 7 65.26 -3.26 -2.04696 00 65.26 0.74 0.46465 65.26 -0.26 -0.16325 10 63.716 -0.716 -0.44958 11 66.032 1.968 1.23571\fUse Excel to obtain the following values: [A] What is the value of the slope for the regression equation when predicting women's heights from men's heights? [B] Obtain the value of the v intercepL (C) Provide an interpretation of the y intercept obtained in part E. (El) Create a scatterplot for the data above and plot the regression line. {E} What are the predicted heights for wives whose husbands" heights are: TD. 59. and 5??