vault backup: 2024-03-04 12:41:03
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Probability histograms represent *chance*. Each class interval represents the probability an event would occur. As the number of repetitions increases, the closer the graphed data will appear to the calculated probability histogram.
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Probability histograms represent *chance*. Each class interval represents the probability an event would occur. As the number of repetitions increases, the closer the graphed data will appear to the calculated probability histogram.
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The probability curve for the *sum of draws* will approximately follow the normal curve if the number of draws is large enough, even if the tickets in the box *do not *follow the normal curve.
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The probability curve for the *sum of draws* will approximately follow the normal curve if the number of draws is large enough, even if the tickets in the box *do not follow the normal curve.
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When applying statistics to sums, it's usually in the form of *how much do we think the sum will add up to*, then compared against what it actually adds up to. The $EV_{sum}$ is used for for the estimated sum of all events. The $SE_{sum}$ refers to the standard error of the sum, or how much you expect the guess to be off by. This can be thought of like the standard deviation.
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When applying statistics to sums, it's usually in the form of *how much do we think the sum will add up to*, then compared against what it actually adds up to. The $EV_{sum}$ is used for for the estimated sum of all events. The $SE_{sum}$ refers to the standard error of the sum, or how much you expect the guess to be off by. This can be thought of like the standard deviation.
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