Q3 The personnel director for Electronics Associates developed the following estimated regression equation relating an employee's score on a job satisfaction test to his or her length of service and wage rate . Regression Analysis hat y =14.4-8.69 x 1 +0.005 x 2 Where x 1 =x 2 = hat y = length of service ( years wage rate ( dollars ) job satisfaction test score ( higher scores indicate greater job satisfaction ) ANOVA SS MS Source Regression Error Total 7 71.17 720.0 Regression Output Std . Error 8.191 1.555 Variables Constants Coefficients 2.085 a . Compute the missing entries in this output . b . Use the F test at 0.05 significance level to see whether a significant relationship is present . c . Use the t test at 0.05 significance level to test . d . Predict the job satisfaction test score for an employee who has four years of service and makes S6.50 per hour H0:BI=0

Q3: The personnel director for Electronics Associates developed the following estimated regression equation relating an employee's score on a job satisfaction test to his or her length of service and wage rate. Regression Analysis y = 14.4- 8.69 x, + 0.005 x2 Where x, = length of service (years) x, = wage rate (dollars) * =job satisfaction test score (higher scores indicate greater job satisfaction) ANOVA Source DF SS MS F Regression Error 71.17 Total 7 720.0 Regression Output Variables Coefficients Std. Error Constants 8.191 X1 1.555 X2 2.085 a. Compute the missing entries in this output. b. Use the F test at 0.05 significance level to see whether a significant relationship is present. c. Use the f test at 0.05 significance level to test HO: B/ = 0. d. Predict the job satisfaction test score for an employee who has four years of service and makes $6.50 per hour