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Apply Principles of the Multiple Regression Model Building Process A) Model 2 Explains Less of the Variability in Average

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Apply principles of the multiple regression model building process.
-A sample of 30 companies was randomly selected for a study investigating what
Factors affect the size of company bonuses. Data were collected on the number of
Employees at the company and whether or not the employees were unionized (1 = yes,
0 = no) . Multiple regression output is shown below for two competing models. Which
Of the following statements is true?  Model 1:  Dependent Variable is Average Annual Bonus  Predictor  Coef  SE Coef  T  P  Constant 347.9872.20.400.693 Employees 0.65470.11055.920.000 Union 1259.5605.82.080.047S=1631.56RSq=62.48RSq(adjj) =59.6% Model 2:  Dependent Variable is Average Annual Bonus  Predictor  Coef  SE Coef  T  P  Constant 1241.0982.31.260.218 Employees 0.88720.13186.730.000 Union 525315793.330.003 Emp*Union 0.054240.020122.700.012S=1469.91RSq=70.68RSq(adj) =67.2%\begin{array} { l } \underline{\text { Model 1: }} \\\text { Dependent Variable is Average Annual Bonus } \\\\\begin{array} { l r r r r } \text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \\\text { Constant } & 347.9 & 872.2 & 0.40 & 0.693 \\\text { Employees } & 0.6547 & 0.1105 & 5.92 & 0.000 \\\text { Union } & 1259.5 & 605.8 & 2.08 & 0.047\end{array} \\\\S = 1631.56 \quad \mathrm { R } - \mathrm { Sq } = 62.48 \quad \mathrm { R } - \mathrm { Sq } ( \mathrm { adj } \mathrm { j } ) = 59.6\% \\\\\underline{ \text { Model 2: } } \\\text { Dependent Variable is Average Annual Bonus } \\\\\begin{array} { l r r r r } \text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \\\text { Constant } & - 1241.0 & 982.3 & - 1.26 & 0.218 \\\text { Employees } & 0.8872 & 0.1318 & 6.73 & 0.000 \\\text { Union } & 5253 & 1579 & 3.33 & 0.003\end{array} \\\begin{array} { l l l l l } \text { Emp*Union } & - 0.05424 & 0.02012 & - 2.70 & 0.012\end{array} \\\\S = 1469.91 \quad \mathrm { R } - \mathrm { Sq } = 70.68 \quad \mathrm { R } - \mathrm { Sq } ( \mathrm { adj } ) = 67.2\% \\\end{array}


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