Undergrad Basic standard deviation calculation

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The discussion focuses on the calculation of standard deviation (SD) and its relationship with rate and time. It clarifies that the standard deviation of total counts (n) is expressed as √n, while the rate (r) is defined as n/t. The equations presented demonstrate how changes in counts (Δn) and rate (Δr) relate to time. The conversation highlights the importance of squaring in the denominator for accurate calculations. Overall, the thread emphasizes understanding the foundational equations for standard deviation in relation to counts and rates.
Graham87
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I don’t get how they got the equation for the standard deviation. Why do they only square with the time in the denominator?

Thanks!

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We know that the SD of the total number of counts n is √n and rate r =n/t

So;
n=rt
Δn = (Δr)⋅t =√(n/t)t
Δr=√(n)/t =√(n/t2)
 
gleem said:
We know that the SD of the total number of counts n is √n and rate r =n/t

So;
n=rt
Δn = (Δr)⋅t =√(n/t)t
Δr=√(n)/t =√(n/t2)
Aha! Thanks!
 
The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...

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