Probability density for related variables

AI Thread Summary
The discussion revolves around calculating the probability density of magnetization (M) in a system of spins, where the probabilities of spins being up or down are equal. The user initially calculates the probability density for m spins up using the formula for binomial distribution. They propose substituting m with (M+N)/2 to express the probability density in terms of M, acknowledging that M can range from -N to N. However, a caution is raised regarding the consideration of parity in the calculations. The conversation highlights the importance of understanding the mathematical properties of probability densities in this context.
diegzumillo
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Homework Statement


Say I calculated a probability density of a system containing m spins up (N is the total number of particles). The probabilities of being up and down are equal so this is easy to calculate. Let's call it ##\omega_m##. Then we define magnetization as ##M=2m-N## and it asks me to calculate the probability density of M.

Homework Equations


##\omega_m(m)=\frac{1}{2^N}\frac{N!}{m!(N-m)!}##

The Attempt at a Solution


I'm not sure how to interpret a probability density of M. M can have a value between -N and N, so the probability, for example, of M=-N is the same as m=0. This suggests me that I can simply replace m for (M+N)/2 in its probability density expression. I don't know if that makes sense, the mathematical properties of these probability densities are no where to be found (at least not with this particular detail).
 
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I think my comprehensioon of that probability density improved a bit. It's the probability of the system to be in the state defined by N and m (or M), so my solution obtained from simply rewriting ##\omega## as ##\omega(N,M)## is right. Right?
 
diegzumillo said:
This suggests me that I can simply replace m for (M+N)/2 in its probability density expression.
Yes, except consider parity.
 
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