The Rule of five:

The normal with means np and np q can be used to approximate the binomial distribution with parameters n and p if \(npq > 5\).

Here, \(n = 1,000\),\(p = 0.001\).

\(npq = 1,000 \times 0.001 \times 0.999 = 0.999 <5\)</span>

Normal approximation cannot be used for the binomial distribution with \(n = 1,000\),\(p = 0.001\).

The direct approximation of the binomial by Poisson says that the binomial distribution with parameters n and p has the same distribution as the Poisson with the parameter np when npis large.

The value of np is obtained as shown below:

np = 1,000 \times 0.001=1

Since the value of n is large and p is small and the value of np is small, the binomial distribution can be approximated to Poisson.

That is, the binomial distribution with \(n = 1,000\), \(p = 0.001\) cannot be approximated to a normal distribution and it can be approximated to a Poisson distribution.

The normal with means np and np q can be used to approximate the binomial distribution with parameters n and p if \(npq > 5\).

Here, \(n = 1,000\),\(p = 0.001\).

\(npq = 1,000 \times 0.001 \times 0.999 = 0.999 <5\)</span>

Normal approximation cannot be used for the binomial distribution with \(n = 1,000\),\(p = 0.001\).

The direct approximation of the binomial by Poisson says that the binomial distribution with parameters n and p has the same distribution as the Poisson with the parameter np when npis large.

The value of np is obtained as shown below:

np = 1,000 \times 0.001=1

Since the value of n is large and p is small and the value of np is small, the binomial distribution can be approximated to Poisson.

That is, the binomial distribution with \(n = 1,000\), \(p = 0.001\) cannot be approximated to a normal distribution and it can be approximated to a Poisson distribution.