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[Math] Developing methods for determining the balance and reliability of dice.
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<blockquote data-quote="tarchon" data-source="post: 1061341" data-attributes="member: 5990"><p>SD isn't a measurement of the width of any peak, and it's really not even a measurement. If you're measuring something, it's technically an estimator of a parameter, not the parameter itself. SD is the square root of the variance, the expectation of the square of the deviation from the mean (also called the 2nd central moment)</p><p>sqrt(E[(x-μ )<sup>2</sup>]). With certain unimodally peaked distributions like the normal, this corresponds to the width of the peak, but it's neither the definition nor the underlying sense of what SD is. As the name roundaboutly implies, it represents how much the random variable or process tends to deviate from the mean.</p><p>Uniform distributions have it and they've got quite a lot of it.</p></blockquote><p></p>
[QUOTE="tarchon, post: 1061341, member: 5990"] SD isn't a measurement of the width of any peak, and it's really not even a measurement. If you're measuring something, it's technically an estimator of a parameter, not the parameter itself. SD is the square root of the variance, the expectation of the square of the deviation from the mean (also called the 2nd central moment) sqrt(E[(x-μ )<sup>2</sup>]). With certain unimodally peaked distributions like the normal, this corresponds to the width of the peak, but it's neither the definition nor the underlying sense of what SD is. As the name roundaboutly implies, it represents how much the random variable or process tends to deviate from the mean. Uniform distributions have it and they've got quite a lot of it. [/QUOTE]
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[Math] Developing methods for determining the balance and reliability of dice.
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