Use the output to write the regression equation.

2. Given the regression equation, how much Job Success would a person experience if they typed 56 Words per Minute on the employment test?

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Regression Model 1 Model 1 a. Dependent Variable: Job_Success b. All requested variables entered. Variables Entered/Removedª Variables Removed Model 1 Variables Entered Words_Typed b Model 1 R .749ª Model Summary a. Predictors: (Constant), Words_Typed Regression Residual R Square .561 Sum of Squares 54.548 42.652 Total 97.200 a. Dependent Variable: Job_Success b. Predictors: (Constant), Words_Typed Adjusted R Square Method -2.872 .170 Enter ANOVA (Constant) Words Typed a. Dependent Variable: Job_Success .537 df 1 18 19 Std. Error of the Estimate 1.539 Mean Square 54.548 2.370 Coefficients Unstandardized Coefficients B Std. Error 1.717 .035 Standardized Coefficients Beta .749 F 23.020 t -1.672 4.798 Sig. .000b Sig. 112 .000 Regression Model 1 Model 1 a. Dependent Variable: Job_Success b. All requested variables entered. Variables Entered/Removedª Variables Removed Model 1 Variables Entered Words_Typed b Model 1 R .749ª Model Summary a. Predictors: (Constant), Words_Typed Regression Residual R Square .561 Sum of Squares 54.548 42.652 Total 97.200 a. Dependent Variable: Job_Success b. Predictors: (Constant), Words_Typed Adjusted R Square Method -2.872 .170 Enter ANOVA (Constant) Words Typed a. Dependent Variable: Job_Success .537 df 1 18 19 Std. Error of the Estimate 1.539 Mean Square 54.548 2.370 Coefficients Unstandardized Coefficients B Std. Error 1.717 .035 Standardized Coefficients Beta .749 F 23.020 t -1.672 4.798 Sig. .000b Sig. 112 .000 Regression Model 1 Model 1 a. Dependent Variable: Job_Success b. All requested variables entered. Variables Entered/Removedª Variables Removed Model 1 Variables Entered Words_Typed b Model 1 R .749ª Model Summary a. Predictors: (Constant), Words_Typed Regression Residual R Square .561 Sum of Squares 54.548 42.652 Total 97.200 a. Dependent Variable: Job_Success b. Predictors: (Constant), Words_Typed Adjusted R Square Method -2.872 .170 Enter ANOVA (Constant) Words Typed a. Dependent Variable: Job_Success .537 df 1 18 19 Std. Error of the Estimate 1.539 Mean Square 54.548 2.370 Coefficients Unstandardized Coefficients B Std. Error 1.717 .035 Standardized Coefficients Beta .749 F 23.020 t -1.672 4.798 Sig. .000b Sig. 112 .000 Regression Model 1 Model 1 a. Dependent Variable: Job_Success b. All requested variables entered. Variables Entered/Removedª Variables Removed Model 1 Variables Entered Words_Typed b Model 1 R .749ª Model Summary a. Predictors: (Constant), Words_Typed Regression Residual R Square .561 Sum of Squares 54.548 42.652 Total 97.200 a. Dependent Variable: Job_Success b. Predictors: (Constant), Words_Typed Adjusted R Square Method -2.872 .170 Enter ANOVA (Constant) Words Typed a. Dependent Variable: Job_Success .537 df 1 18 19 Std. Error of the Estimate 1.539 Mean Square 54.548 2.370 Coefficients Unstandardized Coefficients B Std. Error 1.717 .035 Standardized Coefficients Beta .749 F 23.020 t -1.672 4.798 Sig. .000b Sig. 112 .000

Answer rating: 100% (QA)

The regression results show that there is a significant positive relationship between words typed and job success Rsquared 0749 p 0000 This means that people who type more words per minute are more li... View the full answer