Question 80 1.5 pts For Q83-Q89 (For Model 2) Model 2 Model Summary Adjusted R Std. Error of Model R R Square Square the Estimate 2 .914 836 .817 2.08214 a. Predictors: (Constant), Bachelor_Degree, Years_in_Business ANOVA" Sum of Model Squares df Mean Square Sig 2 Regression 375.250 187.625 43.278 .000 Residual 73.700 4.335 Total 448.950 19 a. Dependent Variable: Numbers_Homes_Sold b. Predictors: (Constant), Bachelor_Degree, Years_in_Business Coefficients Standardized Unstandardized Coefficients Coefficients Model Std. Error Beta Sig. 2 Constant .832 1.016 818 425 Years_in_Busines .686 .108 .736 6.361 000 Bachelor_Degree 2.662 1.101 .279 2.417 .027 a. Dependent Variable: Numbers_Homes_Sold How well (%) does the data fit a simple linear regression model 2? O 88.3% O 77.9% O 83.6% O 91.4%Model 2 Model Summary Adjusted R Std. Error of Model R R Square Square the Estimate .914 .836 .817 2.08214 . Predictors: (Constant). Bachelor_Degree, Years_in_Business ANOVA Sum of Model Squares of Mean Square sig. Regression 375.250 187.625 43.278 .000 Residual 73.700 4.335 Total 448.950 a. Dependent Variable: Numbers_Homes_Sold b. Predictors: (Constant). Bachelor_Degree, Years_in_Business Coefficients Standardized Unstandardized Coefficients Coefficients Model Std. Error Beta Sig. (Constant) .832 1.016 .818 .425 Years_in_Busines 586 108 .736 6.361 .000 Bachelor_Degree 2.662 1.101 .279 2.417 027 a. Dependent Variable: Numbers_Homes_Sold How well (%) does the data fit a simple linear regression model 2? O 88.3% O 77.9% O 83.6% O 91.4% Question 81 1 pts What number is the coefficient (B2) of Bachelor_Degree variable in model 2? O 0.686 O 0.823 O 0.943 O 2.662Question 82 1 pts Is the following statement about the interpretation of the coefficient of of Bachelor_Degree variable in model 2 correct? "Having a bachelor degree could increase number of homes sold by 2.662" O Yes O No Question 83 1 pts Based on the SPSS output Model 2, do you think the coefficient (B2) of Bachelor_Degree variable in model 2 is statistically different from zero? O Yes O No Question 84 1 pts In Model 2, the researcher compares the effect of two variables (years in business and bachelor degree variables) on number of home sold. Which variable has higher effect on the number of home sold? O Years in business variable O Bachelor degree variable Question 85 1 pts In Model 2, if the individual has ten years in the business and a bachelor degree, how many numbers of homes sold are approximately predicted? (Round it down to whole number) 0 3 6 0 7 O 10Comparing between Model 1 and Model 2, which model is the better model? Model 1 Model Summary Adjusted R Std. Error of Model R R Square Square the Estimate .883 779 .767 2.34553 a. Predictors: (Constant), Years_in_Business ANOVA Sum of Model Squares df Mean Square Sig. Regression 349.923 349.923 63.605 .000 Residual 99.027 18 5.502 Total 448.950 19 a. Dependent Variable: Numbers_Homes_Sold b. Predictors: (Constant), Years_in_Business Coefficients Standardized Unstandardized Coefficients Coefficients Model Std. Error Beta Sig. (Constant) .943 1.144 .824 421 Years_in_Busines .823 .103 .883 7.975 .000 a. Dependent Variable: Numbers_Homes_Sold Model 2 Model Summary Adjusted R Std. Error of Model R R Square Square the Estimate 2 .914 836 .817 2.08214 a. Predictors: (Constant). Bachelor_Degree, Years_in_Business ANOVA Sum of Model Squares df Mean Square Sig. 2 Regression 375.250 187.625 43.278 .000 Residual 73.700 17 4.335 Total 448.950 19 a. Dependent Variable: Numbers_Homes_Sold b. Predictors: (Constant). Bachelor_Degree, Years_in_Business Coefficients Standardized Unstandardized Coefficients Coefficients Model Std. Error Beta Sig. (Constant) 832 1.016 .818 .425 Years_in_Busines 686 108 .736 6.361 .000 Bachelor_Degree 2.662 1.101 .279 2.417 .027 a. Dependent Variable: Numbers_Homes_Sold O Model 1 O Model 2
