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I am trying to compute probability, and I give a:

$$\sum^{25}_{k=0}\binom {3000}{k} p^k (1-p)^{3000-k}$$

$$p=0,0001$$$

Is there a smart way to compute it? Another else, I am thinking about Poisson. What do you think?

user180834
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3 Answers3

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The ratio of two successive terms of the sum is

$$\frac p{1-p}\frac{3000-k+1}{k}<0.3$$as of $k=2$.

As $0.3^{25}<10^{-13}$, the tail is neglectible and the sum is $1$.

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You're on the right track. If $p=c/n$, then $\binom{n}{k}p^k(1-p)^{n-k}\rightarrow e^{-c}\frac{c^k}{k!}$. In other words, the binomial distribution goes to a Poisson for rare events. You can use the above approximation to get a quick estimate, which is equivalent to asking $P(X\le25)$ for a Poisson with $n=3000$, giving $c=0.3$. Only the first few terms will matter.

Alex R.
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I use the approximation results given here:

Let $\mu=3000 \times 0.0001 =0.3$ and $\sigma^2=3000\times 0.0001 \times (1-0.0001)=0.29997.$ Now note that $$\frac{X-\mu}{\sigma}\sim N(0,1)$$ thus $$\Pr(X\leq 25)=\Pr\Big(\frac{X-0.3}{\sqrt{0.29997}}\le\frac{25-0.3}{\sqrt{0.29997}}\Big)\simeq \Pr\Big(Z\le45.0981\Big)\simeq 1, $$where $Z\sim N(0,1).$

Math-fun
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  • In this case $n$ is not nearly large enough to eliminate the skew from the distribution. The outcome $0$ occurs with probability $74$% (approximately) and all other outcomes with non-zero probability are greater. Fortunately $k=25$ is so far out on the rapidly-vanishing tail of this distribution that it doesn't much matter what kind of approximation you use. – David K Mar 17 '15 at 21:42
  • @DavidK I see, very interesting point about the skewness, in fact here the skewness turns out to be 1.82547, far from being zero as you mentioned. Many thanks! – Math-fun Mar 17 '15 at 21:59