Prob. for average value or less in binomial distribution?

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Discussion Overview

The discussion revolves around estimating the probability that a binomial distribution yields an average value of np or less. Participants explore closed form expressions, approximations, and specific cases, focusing on theoretical aspects of probability distributions.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning

Main Points Raised

  • One participant inquires about a closed form expression or estimate for the probability P that a binomial distribution yields np or less, presenting a specific sum to evaluate.
  • Another participant notes that there is no closed form expression for the probability other than the exact formula, but suggests that for large n, the binomial distribution can be approximated by the normal distribution when p is fixed.
  • A different participant claims that for the case of p=1/n, the sum converges to 2/e (approximately 73%) as n approaches infinity.
  • One participant reiterates the lack of a closed form expression and discusses the normal approximation yielding 50%, which they argue is inaccurate due to the discrete nature of the distribution. They express uncertainty about applying the Poisson approximation with respect to the variables n and p.
  • Another participant expresses confusion about how to incorporate the variables n and p into the Poisson distribution, noting that the mean of the Poisson distribution is np.

Areas of Agreement / Disagreement

Participants do not reach a consensus, as there are multiple competing views regarding the approximations and expressions for the probability in question. Uncertainties about the application of the Poisson distribution and the implications of the normal approximation remain unresolved.

Contextual Notes

There are limitations regarding the assumptions made about the distributions, particularly in how the normal and Poisson approximations apply to the binomial distribution under different conditions.

Gerenuk
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Hello!
Is there a closed form expression or a good estimate for the probability that a binomial distribution yield the average np or less. Basically I'm asking for a good way to evaluate
<br /> P=\sum_{k=0}^{np} \begin{pmatrix} n\\ k<br /> \end{pmatrix} p^k(1-p)^{n-k}<br />

I just figured that for the simplified case p=\frac{1}{n} this probability converges to 63% for large n. What about more general cases?
 
Last edited:
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There is no closed form expression for Prob. (other than the exact formula). However for large n, the binomial can be approximated by the normal distribution when p is fixed. In the case you are describing (np fixed), the Poisson distribution is a good approximation.
 
For the simplified case of p=1/n, your sum goes to 2/e (about 73%) as n->infty.
 
mathman said:
There is no closed form expression for Prob. (other than the exact formula). However for large n, the binomial can be approximated by the normal distribution when p is fixed. In the case you are describing (np fixed), the Poisson distribution is a good approximation.
Unfortunately using the normal distribution yields 50%, which is not true when the discrete character isn't lost. For Poisson I'm not sure where to put in my 2 variables n and p :(

Btw, this problem I thought of when trying to think of how likely a "statistical statement" would be. With the odds 1:N for example you can be 63% (1-e^{-1}) sure that at least 1 of a N people is "positive".
 
Last edited:
For Poisson I'm not sure where to put in my 2 variables n and p
Mean(Poisson) = np.
 

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