Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .090a .008 .007 39.120 a. Predictors: (Constant), hours study per week ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 16017.305 1 16017.305 10.466 .001b Residual 1943612.015 1270 1530.403 Total 1959629.320 1271 a. Dependent Variable: time 1 delinquency scale b. Predictors: (Constant), hours study per week Coefficientsa Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 (Constant) 29.718 1.502 19.791 <.001 hours study per week -.490 .151 -.090 -3.235 .001 a. Dependent Variable: time 1 delinquency scale
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490. This means that for every additional hour studied per week, the delinquency score decreases by 0.490, on average, holding all other variables constant. This is a statistically significant relationship, as indicated by the significance level (Sig.) of 0.001, Show more…
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Summary Output Regression Statistics Multiple R: 0.7732 R Square: 0.5978 Adjusted R Square: 0.5476 Standard Error: 3.0414 Observations: 10 ANOVA df SS MS F Significance F Regression: 1 110 110 11.892 0.009 Residual: 8 74 9.25 Total: 9 184 Coefficients Standard Error t Stat P-value Intercept: 39.222 5.942 6.600 0.000 x: -0.556 0.161 -3.448 0.009 e. 59.783% of the variability in Y is explained by the variability in X. a. What has been the sample size for the above? b. Perform a t test and determine whether or not X and Y are related. Let α = 0.05. c. Perform an F test and determine whether or not X and Y are related. Let α = 0.05. d. Compute the coefficient of determination. e. Interpret the meaning of the value of the coefficient of determination that you found in d. Be very specific.
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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?
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Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .864a .747 .691 .87153 ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 20.164 2 10.082 13.273 .002b Residual 6.836 9 .760 Total 27.000 11 Coefficientsa Unstandardized Coefficients Standardized Coefficients t Sig. Model B Std. Error Beta 1 (Constant) -8.883 3.266 -2.720 .024 icecream -.050 .080 -.171 -.634 .542 weather .205 .056 .992 3.675 .005 a. Dependent Variable: crime
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