3. Consider n independent observations X1,..., X, of a Poisson random variable with param- eter 1. (a) Use Chebyshev's inequality to evaluate the minimum number of observations needed to achieve 1 Xị. i=1 P(|Xn- A| < 0.01) > 0.9, where Xn n (b) Repeat the computations using the Central Limit Theorem. Note: Remember that the Poisson distribution is a discrete distribution with PMF fx(x; A) х! where xe {0,1,2,3,……}, and 1 > 0 and hence E(X) = A , and Var(X) = A.

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3. Consider n independent observations X1,..., X, of a Poisson random variable with param-
eter A.
(a) Use Chebyshev's inequality to evaluate the minimum number of observations needed
to achieve
п
1
P(|Xn– A|< 0.01) > 0.9,
where Xn
ΣΧ.
п
i=1
(b) Repeat the computations using the Central Limit Theorem.
Note:
Remember that the Poisson distribution is a discrete distribution with PMF
fx(x;A) =
х!
where xe {0,1,2,3, .}, and 1 > 0
and hence E(X) = A , and Var (X) = A.
Transcribed Image Text:3. Consider n independent observations X1,..., X, of a Poisson random variable with param- eter A. (a) Use Chebyshev's inequality to evaluate the minimum number of observations needed to achieve п 1 P(|Xn– A|< 0.01) > 0.9, where Xn ΣΧ. п i=1 (b) Repeat the computations using the Central Limit Theorem. Note: Remember that the Poisson distribution is a discrete distribution with PMF fx(x;A) = х! where xe {0,1,2,3, .}, and 1 > 0 and hence E(X) = A , and Var (X) = A.
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