000714 1523239 0129454 0000321 0002496 putts

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Unformatted text preview: 0.001132 - 0.010997 0.991238 - 0.002246 0.002221 0.001087 0.000714 1.523239 0.129454 - 0.000321 0.002496 Putts Save Percentage ˆ Estimated regression equation: y = 0.51205 + 0.00471GIR – 0.45012Putts + 0.00057DDist – 0.000012DAcc + 0.00109SavePercentage b) R square = 0.1111 or approximately 11%. Thus only 11% of the variation in log earnings per event can be explained these five predictor variables. c) From the coefficients it appears that higher scores on GIR and DDist and SavePercentage are associated with greater earnings, while lower scores on Putts and DAcc are associated with great earnings. Of these, the surprising one is DAcc, meaning that less accuracy in drives leads to greater earnings. However, the coefficient is not significant which means that this interpretation is not supported statistically. In fact, only GIR and Putts are statistically significant predictors in the fitted model so they are the only two that should be interpreted. For each increase of 1% in GIR, the log earnings per event increases by 0.004713. For ea...
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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 UBC.

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