How to Derive Uncertainty from Mean and RMS?

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SUMMARY

The discussion focuses on deriving uncertainty from a function defined as F = os - ss, where os and ss represent opposite-sign and same-sign binomial distributions, respectively. The mean is calculated using the formula N(total) * (2*prob(os) - 1), while the root mean square (RMS) is determined by 2 * SQRT{N(total) * prob(os) * (1 - prob(os))}. The participant seeks to establish a relationship between variance and uncertainty, confirming that RMS is indeed the square root of variance.

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penguindecay
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Dear Reader,

Earlier I posted a topic on the uncertainty of a function that is F = os - ss , where os and ss are opposite-sign and same-sign, and are both binomial distributions. I want to know the uncertainty of my F,

I have found a equation for the mean, and rms of my function which are:

N(total) * (2*prob(os) -1 ) for the mean and

2 * SQRT { N(total) * prob(os) * (1 - prob(os)) } for the rms

where N(total) = os+ss

Is it possible to get an equation for the variance or uncertainty from the given information?

Thank you for reading

Kim
 
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I am not sure what you are looking for. However rms is simply the square root of the variance.
 
mathman said:
I am not sure what you are looking for. However rms is simply the square root of the variance.

I am looking for the square root of the variance, and if it is as you state the rms equation I have, then thank you.
 

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