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"Jerry Avins" <[EMAIL PROTECTED]> wrote in message news:[EMAIL PROTECTED] > Clay S. Turner wrote: > > ... > > > Now for a simple example. Let's say you have a fair die. Each time you toss > > it, the probabily of each outcome is 1/6. So theory says we have a uniform > > distribution. Now toss the die 100 times and count how many times each value > > shows up. Now theory says on average each value shows up 1/6 of the time. > > However in any given sample (set of measurements), you can't expect this > > perfect a distribution every time. Why you ask? That is because each trial > > is independent of the prior ones. And in this situation I only tossed it 100 > > times and 100 is not a multiple of six, so not all bins can have the same > > number of counts. Since the counts must be integers and 100/6 = 16.6666666, > > you can see the one problem. > > ... > > This can raise an unrealistic expectation. If we toss the die 102 times, > can we then ask that each face of an honest die to turn up 17 times? Jerry, Yes, we can ask but this will only happen about once every 49300 times. I was trying to illustrate two different points, the first was the case where the number of die values doesn't divide evenly into the sample size. And the other which is the more important is the case where we don't expect each value (face value on a die) to show up in perfectly matched counts in trial runs. I know that you know this, but I think Walala now gets the point - I hope. Clay > > Jerry > -- > Engineering is the art of making what you want from things you can get. > ŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻŻ >
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