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Which of the following statements is the CORRECT expression in APA format of the SPSS simple linear regression results provided below? Model 1 R .904ª Model 1 Model Summary Model 1 .756 a. Predictors: (Constant), Experience years (year) Regression Residual Total R Square .817 Sum of Squares 4.900 1.100 6.000 Adjusted R Square ANOVA df 1 3 4 a. Dependent Variable: Income (10 million VND/month) b. Predictors: (Constant), Experience years (year) Coefficients -100 700 Unstandardized Coefficients B Std. Error (Constant) Experience years (year) a. Dependent Variable: Income (10 million VND/month) Mean Square 4.900 .367 Std. Error of the Estimate .606 .635 191 F 13.364 Standardized Coefficients. Beta .904 t -.157 3.656 Sig. .035b Sig. 885 .035 A regression analysis was conducted with Experience Years as criterion variable and Income as the predictor. Income was a significant predictor of Experience Years, 3-3.66, t(82)=0.90, p<0.05, and accounted for 3.50% of the variance in Experience Years. A regression analysis was conducted with Income as criterion variable and Experience Years as the predictor. Experience Years was a NOT significant predictor of Income, B=0.90, t(4)=3.66, p>0.05, and accounted for 81.70% of the variance in Income scores. A regression analysis was conducted with Experience Years as criterion variable and Income as the predictor. Income was NOT a significant predictor of Experience Years, 3-3.66, t(82)=0.90, p<0.05, and accounted for 3.50% of the variance in Experience Years. A regression analysis was conducted with Income as criterion variable and Experience Years as the predictor. Experience Years was a significant predictor of Income, B=0.90, t(4)=3.66, p<0.05, and accounted for 81.70% of the variance in Income scores.

Which of the following statements is the CORRECT expression in APA format of the SPSS simple linear regression results provided below? Model 1 R .904ª Model 1 Model Summary Model 1 .756 a. Predictors: (Constant), Experience years (year) Regression Residual Total R Square .817 Sum of Squares 4.900 1.100 6.000 Adjusted R Square ANOVA df 1 3 4 a. Dependent Variable: Income (10 million VND/month) b. Predictors: (Constant), Experience years (year) Coefficients -100 700 Unstandardized Coefficients B Std. Error (Constant) Experience years (year) a. Dependent Variable: Income (10 million VND/month) Mean Square 4.900 .367 Std. Error of the Estimate .606 .635 191 F 13.364 Standardized Coefficients. Beta .904 t -.157 3.656 Sig. .035b Sig. 885 .035 A regression analysis was conducted with Experience Years as criterion variable and Income as the predictor. Income was a significant predictor of Experience Years, 3-3.66, t(82)=0.90, p<0.05, and accounted for 3.50% of the variance in Experience Years. A regression analysis was conducted with Income as criterion variable and Experience Years as the predictor. Experience Years was a NOT significant predictor of Income, B=0.90, t(4)=3.66, p>0.05, and accounted for 81.70% of the variance in Income scores. A regression analysis was conducted with Experience Years as criterion variable and Income as the predictor. Income was NOT a significant predictor of Experience Years, 3-3.66, t(82)=0.90, p<0.05, and accounted for 3.50% of the variance in Experience Years. A regression analysis was conducted with Income as criterion variable and Experience Years as the predictor. Experience Years was a significant predictor of Income, B=0.90, t(4)=3.66, p<0.05, and accounted for 81.70% of the variance in Income scores.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Which of the following statements is the CORRECT expression in APA format of the SPSS simple linear regression results provided below? Model 1 R .904ª Model 1 Model Summary Model 1 .756 a. Predictors: (Constant), Experience years (year) Regression Residual Total R Square .817 Sum of Squares 4.900 1.100 6.000 Adjusted R Square ANOVA df 1 3 4 a. Dependent Variable: Income (10 million VND/month) b. Predictors: (Constant), Experience years (year) Coefficients -.100 .700 Unstandardized Coefficients B Std. Error (Constant) Experience years (year) a. Dependent Variable: Income (10 million VND/month) Mean Square 4.900 .367 Std. Error of the Estimate .606 .635 191 F 13.364 Standardized Coefficients Betal .904 t -.157 3.656 Sig. .035b Sig. .885 .035 A regression analysis was conducted with Experience Years as criterion variable and Income as the predictor. Income was a significant predictor of Experience Years, 3=3.66, t(82)=0.90, p<0.05, and accounted for 3.50% of the variance in Experience Years. A regression analysis was conducted with Income as criterion variable and Experience Years as the predictor. Experience Years was a NOT significant predictor of Income, 3=0.90, t(4)=3.66, p>0.05, and accounted for 81.70% of the variance in Income scores. A regression analysis was conducted with Experience Years as criterion variable and Income as the predictor. Income was NOT a significant predictor of Experience Years, B-3.66, t(82)=0.90, p<0.05, and accounted for 3.50% of the variance in Experience Years. A regression analysis was conducted with Income as criterion variable and Experience Years as the predictor. Experience Years was a significant predictor of Income, 3=0.90, t(4)=3.66, p<0.05, and accounted for 81.70% of the variance in Income scores.
Transcribed Image Text:Which of the following statements is the CORRECT expression in APA format of the SPSS simple linear regression results provided below? Model 1 R .904ª Model 1 Model Summary Model 1 .756 a. Predictors: (Constant), Experience years (year) Regression Residual Total R Square .817 Sum of Squares 4.900 1.100 6.000 Adjusted R Square ANOVA df 1 3 4 a. Dependent Variable: Income (10 million VND/month) b. Predictors: (Constant), Experience years (year) Coefficients -.100 .700 Unstandardized Coefficients B Std. Error (Constant) Experience years (year) a. Dependent Variable: Income (10 million VND/month) Mean Square 4.900 .367 Std. Error of the Estimate .606 .635 191 F 13.364 Standardized Coefficients Betal .904 t -.157 3.656 Sig. .035b Sig. .885 .035 A regression analysis was conducted with Experience Years as criterion variable and Income as the predictor. Income was a significant predictor of Experience Years, 3=3.66, t(82)=0.90, p<0.05, and accounted for 3.50% of the variance in Experience Years. A regression analysis was conducted with Income as criterion variable and Experience Years as the predictor. Experience Years was a NOT significant predictor of Income, 3=0.90, t(4)=3.66, p>0.05, and accounted for 81.70% of the variance in Income scores. A regression analysis was conducted with Experience Years as criterion variable and Income as the predictor. Income was NOT a significant predictor of Experience Years, B-3.66, t(82)=0.90, p<0.05, and accounted for 3.50% of the variance in Experience Years. A regression analysis was conducted with Income as criterion variable and Experience Years as the predictor. Experience Years was a significant predictor of Income, 3=0.90, t(4)=3.66, p<0.05, and accounted for 81.70% of the variance in Income scores.
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