Stat mech and binomial distribution

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SUMMARY

The discussion focuses on calculating the probability p(N_A;N) of selecting N_A particles of type A from a total of N particles, utilizing the binomial distribution formula. The participants emphasize the need to apply Stirling's approximation and the Central Limit Theorem (CLT) for large N. The solution involves taking logarithms to simplify the binomial expression and then exponentiating after approximation. The Lindeberg version of the CLT is referenced as a potential approach for this problem.

PREREQUISITES
  • Understanding of binomial distribution and its formula
  • Familiarity with Stirling's approximation
  • Knowledge of the Central Limit Theorem (CLT)
  • Basic logarithmic manipulation techniques
NEXT STEPS
  • Study the application of Stirling's approximation in probability theory
  • Research the Central Limit Theorem and its various formulations
  • Explore examples of binomial distribution in statistical mechanics
  • Review logarithmic properties and their use in simplifying complex expressions
USEFUL FOR

Students and researchers in statistical mechanics, particularly those dealing with probability distributions and large particle systems, will benefit from this discussion.

erogard
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Homework Statement



Suppose that particles of two different species, A and B, can be chosen with
probability p_A and p_B, respectively.

What would be the probability p(N_A;N) that N_A out of N particles are of type A?

The Attempt at a Solution



I figured this would correspond to a binomial distrib:

p_N(N_A) = \frac{N!}{N_A ! (N-N_A)!} p_A^{N_A} p_B^{N-N_A}

Now I'm asked to consider the case where N gets large. Then I need to find p(N_A;N) using 1) Stirling appox. and 2) the central limit theorem.

Not sure how to approach 1) since there are no log in my expression. Actually I don't quite get how to do 2) either. Any help would be much appreciated.
 
Physics news on Phys.org
1) You can introduce the logs! And then remove the logs by exponentiation after you've made the approximation.

2) You should just apply the central limit theorem directly. Do you recall what the CLT says exactly?
 
Matterwave said:
1) You can introduce the logs! And then remove the logs by exponentiation after you've made the approximation.

2) You should just apply the central limit theorem directly. Do you recall what the CLT says exactly?

So I did 1) by taking the log and exponentiating to simplify.

Regarding 2), I'm looking at http://en.wikipedia.org/wiki/Central_limit_theorem and I'm assuming the Linderberg version is the relevant one here. Not too sure how to apply it, however. Do you know of any simpler formulation of the theorem that would apply to my case? My book does not state it formally. Thanks!
 

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