What is the covariance between two binomial distributions?

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SUMMARY

The covariance between two binomial distributions, specifically the empirical cumulative distribution functions (CDFs) \(\hat{F}(s)\) and \(\hat{F}(t)\) for \(s < t\), is defined as \(n^{-1}F(s)(1-F(t))\). This relationship is derived from the properties of binomially distributed random variables, where \(\hat{F}(s)\) is based on a sample size \(n\) and the true CDF \(F(t)\). Understanding this covariance is crucial for statistical analysis involving binomial distributions.

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Matteo_
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Hi everybody!

I have a random iid sample Xi, i=1, ..., n

The empirical cdf of the sample at poin s is

\hat{F}\left(s\right)=n^{-1}\sum_{i=1}^{n}{\textbf{1}_{\left(-\infty, s\right)}\left(x_{i}\right)}

Clearly \hat{F}\left(s\right) is binomially distributed with parameters n and p=F(t) (true cdf).

Now I need to find the covariance between \hat{F}\left(s\right) and \hat{F}\left(t\right) for s<t.

I know that the result is n^{-1}F\left(s\right)\left(1-F\left(t\right)\right)

Any help is very appreciated...

Thanks!
 
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