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The Basics, Starting Out
Long Range for begginers
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<blockquote data-quote="rscott5028" data-source="post: 645057" data-attributes="member: 24624"><p>Your point is well made. But, that's not the actual formula for standard deviation. Google it if you want the formula. Fortunately many chronies and Excel will calculate it for you. </p><p> </p><p>The statistical significance is that with anything resembling a normal distribution (bell curve) such as MV samples... the majority will hover closer to the mean allowing you to estimate the population of future samples, 95% of which will fall within 2 standard deviations above and below the mean and 99% will fall within 3x the standard deviation from the mean. </p><p> </p><p>The smaller the SD, the more tightly grouped the samples are around the mean. As such, a low standard deviation far outweighs ES as a predictor of future performance. </p><p> </p><p>Sorry. I didn't mean to knit pick. But, a lot of guys fixate on ES which only takes one bad sample to throw you totally out of whack. </p><p> </p><p>-- richard</p></blockquote><p></p>
[QUOTE="rscott5028, post: 645057, member: 24624"] Your point is well made. But, that's not the actual formula for standard deviation. Google it if you want the formula. Fortunately many chronies and Excel will calculate it for you. The statistical significance is that with anything resembling a normal distribution (bell curve) such as MV samples... the majority will hover closer to the mean allowing you to estimate the population of future samples, 95% of which will fall within 2 standard deviations above and below the mean and 99% will fall within 3x the standard deviation from the mean. The smaller the SD, the more tightly grouped the samples are around the mean. As such, a low standard deviation far outweighs ES as a predictor of future performance. Sorry. I didn't mean to knit pick. But, a lot of guys fixate on ES which only takes one bad sample to throw you totally out of whack. -- richard [/QUOTE]
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