Poisson Distribution Approximated by Hat-Check Distribution

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Theorem

Let $X$ be a discrete random variable which has the hat-check distribution with parameter $n$.

Then $X$ can be approximated by a Poisson distribution with parameter $\lambda = 1$.


Proof

Let $X$ be as described.

Let $k \ge 0$ be fixed.


Then:

\(\ds \lim_{n \mathop \to \infty} \dfrac 1 {\paren {n - k }!} \sum_{s \mathop = 0}^k \dfrac {\paren {-1}^s} {s!}\) \(=\) \(\ds \lim_{n \mathop \to \infty} \dfrac 1 {\paren {n - \paren {n - k} }!} \sum_{s \mathop = 0}^{n - k} \dfrac {\paren {-1}^s} {s!}\) setting $k = n - k$
\(\ds \) \(=\) \(\ds \frac {1^k} {k!} e^{-1}\) Taylor Series Expansion for Exponential Function and Definition of Poisson Distribution


Hence the result.

$\blacksquare$


Poisson Distribution Approximated by Hat-Check Distribution/Examples

Example: $N = 8$

Let $X$ be a discrete random variable which has the hat-check distribution with parameter $n = 8$.

Then $X$ can be approximated by a Poisson distribution with parameter $\lambda = 1$.