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Use Indicator (Dummy) Variables in Multiple Regression S=0.739664RSq=95.6%RSq(adj)=94.6%S = 0.739664 \quad \mathrm { R } - \mathrm { Sq } = 95.6 \% \quad \mathrm { R } - \mathrm { Sq } ( \mathrm { adj } ) = 94.6 \%

question 2

Multiple Choice

Use indicator (dummy) variables in multiple regression.
-A sample of firms was selected from the high tech industry (Industry = 1) and the
Financial services sector (Industry = 0) . Data were collected on the following variables:
Turnover rate, job growth, number of employees, and innovative index (higher scores
Indicate a more innovative and creative organizational culture) . Below are the multiple
Regression results. The correct interpretation of the coefficient of Industry is Dependent Variable is Turnover Rate

 Predictor  Coef  SE Coef TP Constant 9.24390.787111.740.000 Innovative  Index 0.024020.015241.580.134 Job Growth 0.501270.072876.880.000 Employees 0.00061440.00054611.130.276 Industry 2.83290.46996.030.000\begin{array} { l r r r r } \text { Predictor } & \text { Coef } & \text { SE Coef } & \mathbf { T } & \mathbf { P } \\ \text { Constant } & 9.2439 & 0.7871 & 11.74 & 0.000 \\ \text { Innovative } \text { Index } & - 0.02402 & 0.01524 & - 1.58 & 0.134 \\ \text { Job Growth } & - 0.50127 & 0.07287 & - 6.88 & 0.000 \\ \text { Employees } & 0.0006144 & 0.0005461 & 1.13 & 0.276 \\ \text { Industry } & - 2.8329 & 0.4699 & - 6.03 & 0.000 \end{array}

S=0.739664RSq=95.6%RSq(adj) =94.6%S = 0.739664 \quad \mathrm { R } - \mathrm { Sq } = 95.6 \% \quad \mathrm { R } - \mathrm { Sq } ( \mathrm { adj } ) = 94.6 \%


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