A survey conducted by a research team was to investigate how the education level, tenure in current employment, and age are related to annual income. A sample of 20 employees was selected and the same data as in the previous problem were collected. In addition a multiple linear regression analysis was performed to predict annual income from the other 3 variables. A portion of the output from the analysis is shown below. A survey conducted by a research team was to investigate how the education level, tenure in current employment, and age are related to annual income. A sample of 20 employees was selected and the same data as in the previous problem were collected. In addition a multiple linear regression analysis was performed to predict annual income from the other 3 variables. A portion of the output from the analysis is shown below. Coefficients Intercept -143715.95 Education 10453.28 Standard Error 40424.36 2550.63 t Stat P-value Lower 95% Upper 95% -3.56 4.10 0.00 0.00 -229411.76 -58020.14 5046.18 15860.37 Length of -2555.94 2270.89 -1.13 0.28 -7370.01 2258.14 tenure Age 2625.47 1009.70 2.60 0.02 485.01 4765.93 All other things being equal, if an employee's age increased by one year, how much would we predict their annual income would change (rounded to the nearest integer)? It would increase by $2,625 It would decrease by $2.556 We can't say for sure--it depends on the person's age. It would increase by $10.453 It would increase by $2,689.