Question

Let X1, X2, ... , X30 be a random sample of size 30 from a Poisson distribution with a mean of 2/3. Approximate (a) P 15 < 30 i=1 Xi 22 . (b) P 21 30 i=1 Xi < 27 .

Answer 1

(a) To approximate P(15 < ΣXi < 22), we can use the Central Limit Theorem (CLT) since we have a large enough sample size (n = 30) and the mean and variance of the Poisson distribution are both finite.

First, we need to find the mean and variance of the sample mean, which is also the mean and variance of the Poisson distribution:

μ = λ = 2/3

σ^2 = λ = 2/3

Next, we can standardize the random variable Z = (ΣXi - nμ) / sqrt(nσ^2) to have a standard normal distribution:

Z = (ΣXi - 30(2/3)) / sqrt(30(2/3)) = (ΣXi - 20) / sqrt(20)

Then, we can use a standard normal table or calculator to find the probability:

P(15 < ΣXi < 22) ≈ P(-2.74 < Z < -1.77) ≈ 0.038

Therefore, the approximate probability is 0.038.

(b) To approximate P(21 < ΣXi < 27), we can use the same method with the CLT.

First, we need to find the mean and variance of the sample mean:

μ = λ = 2/3

σ^2 = λ = 2/3

Next, we can standardize the random variable Z = (ΣXi - nμ) / sqrt(nσ^2) to have a standard normal distribution:

Z = (ΣXi - 30(2/3)) / sqrt(30(2/3)) = (ΣXi - 20) / sqrt(20)

Then, we can use a standard normal table or calculator to find the probability:

P(21 < ΣXi < 27) ≈ P(-0.68 < Z < 0.68) ≈ 0.495

Therefore, the approximate probability is 0.495.