Full model y log earnings per event 0333382

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Unformatted text preview: o predict log earnings per event using all five predictor variables. FULL MODEL: Y = Log Earnings per Event 0.333382 0.111144 0.086453 0.051891 186 Significance F Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression df SS 5 180 0.484677 Total 185 0.545281 MS 0.060605 Residual Intercept GIR Coefficients Standard Error 0.512052 0.370436 0.012121 F 0.000686 4.501490 0.002693 t Stat P- value Lower 95% Upper 95% 1.382294 0.168594 - 0.218904 1.243008 0.004713 0.001855 2.541150 0.011893 0.001053 0.008372 - 0.450117 0.168220 - 2.675762 0.008144 - 0.782053 - 0.118180 DDist 0.000573 0.000666 0.859833 0.391025 - 0.000742 0.001887 DAcc - 0.000012...
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This note was uploaded on 01/16/2014 for the course COMM 291 taught by Professor E.fowler during the Fall '10 term at The University of British Columbia.

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