- #1

marco1235

## Main Question or Discussion Point

Good morning PF,

I'm feeling a bit doubtful about this issue. I'm working with optical detectors and I have to characterize them in terms of quantum efficiency and other similar things. Now suppose my detector is, ideally, a single large pixel, which I illuminate for a specific time. Then I store the recorded N

I want to make an average of such 10k values, and that's fine. But how about the uncertainty associated with this repeated measure? I have two ways:

1) computing the standard deviation using std-like function (Matlab)

2) putting N

I'm really stucked in this situation.

Hope someone could help me!

Have a nice day

I'm feeling a bit doubtful about this issue. I'm working with optical detectors and I have to characterize them in terms of quantum efficiency and other similar things. Now suppose my detector is, ideally, a single large pixel, which I illuminate for a specific time. Then I store the recorded N

_{photons}and repeat the procedure for 10k times! At each iteration, due to the randomness of the process I can get 100 counts in the first step, 102 at the second, 95, 87, 101, 106, ... an so on.I want to make an average of such 10k values, and that's fine. But how about the uncertainty associated with this repeated measure? I have two ways:

1) computing the standard deviation using std-like function (Matlab)

2) putting N

_{avg}as argument of the squared-root like in Poisson processesI'm really stucked in this situation.

Hope someone could help me!

Have a nice day