SUMMARY OUTPUT Regression Statistics Multiple R 0.991 R Square 0.982 Adjusted R Square 0.976 Standard Error 0.299 Observations 10 ANOVA df SS MS F Signif F Regression 2 33.4163 16.7082 186.325 0.0001 Residual 7 0.6277 0.0897 Total 9 34.0440 Coeff StdError t Stat P-value Intercept – 0.0861 0.5674 – 0.152 0.8837 GDP 0.7654 0.0574 13.340 0.0001 Price – 0.0006 0.0028 – 0.219 0.8330
Added by Kevin M.
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The Multiple R is the correlation coefficient, which measures the strength and direction of the relationship between the dependent variable and the independent variables. In this case, the Multiple R is 0.991, which indicates a strong positive relationship. Show more…
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SUMMARY OUTPUT Regression Statistics Multiple R 0.971 R-Square 0.943 Adjusted R-Square 0.941 Standard Error 30.462 Observations 51 ANOVA Significance SS MS F P-value Regression 747851.57 373925.79 927.91 9.89E-31 Residual 402.98 9.89E-31 Total 792391 48 50 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 26.79 6.68 4.01 1.60E-30 9.04 10.42 Price of Roses -1.41 9.73 -0.15 1.64E-01 1.23E-31 Disposable Income 1539.66 1789.51 -16.16 2.81 0.34
Adi S.
Regression Statistics Multiple R 0.132 R Square 0.018 Adjusted R Square 0.013 Standard Error 2.653 Observations 235.00 ANOVA df SS MS F Significance F Regression 1.00 29.29 29.29 4.16 0.042 Residual 233.00 1639.62 7.04 Total 234.00 1668.91 Coefficients Standard Error t Stat P-value Intercept 2.91 0.59 4.91 0.000 Value For Money 0.35 0.17 2.04 0.042
Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .972 .945 .933 .860 a. Predictors: (Constant), Importance, Duration ANOVA Model Sum of Squares df Mean Square F Sig. 1 114.264 2 57.132 77.294 .000 b. Dependent Variable: Attitude Predictors: (Constant), Importance, Duration Coefficients Model Unstandardized Coefficients Standardized Coefficients t Sig. 1 (Constant) .337 .595 .567 Duration .481 .764 8.160 .000 Importance .289 .314 3.353 .008 a. Dependent Variable: Attitude Q 1. What does "r" signify here?
T. L.
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