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Quirin detailed the procedures he used for determining a statistically significant deviation from the number of expected winners (either positive or negative) in Appendix A (pages 293-300) of Winning at the Races. I believe that the standard he used was any value that fell above 2.5 (for positive factors) or below -2.5 (for negative factors) for the equation:
(Actual Number of Winners (NW) - Expected Number of Winners (EW)) divided by the square root of (EW (1 - EW/Number of Horses (NH)).
I once asked Mike Nunamaker whether he had applied similar tests to the findings that he came up with in Modern Impact Values. He said that he had not, but that the large sample size upon which his findings were based performed the same function and provided the same assurance as the statistical testing that Quirin conducted on his smaller sample sizes.
I'm not sure that you can draw a hard-and-fast correlation between the results of those tests, and any particular level of impact value. I would say that the tests are the determinative factor. A particular handicapping variable may have a relatively high or low impact value, yet still not fall outside of that -2.5 to +2.5 spread.
Last edited by Overlay; 08-29-2008 at 01:06 PM.
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