Respuesta :
Under the Binomial and Poisson distributions gives approximate result is p → 0 n → ∞.
Unlike, in the case of a Binomial distribution, for a Poisson distribution, the knowledge of number of trials to get the observed number of successes is not required. The Poisson distribution has only one parameter namely “m” the mean number of successes per given unit of time.
The Poisson distribution is often taken as a limiting case of Binomial distribution, under the following conditions.
The number of trails is indefinitely large i.e., n → ∞
The probability of success, “p” is very small i.e., p → 0
np is finite i.e., np = m where p = m/n and q = 1 – m/n and m > 0.
However, it is not defined if “n” is large means how large and “p” is closed to zero means how small? It is left to the readers to assume how large n should be and how small p should be? As mentioned earlier, the Poisson distribution is often described as a limiting case of Binomial distribution.
Based on the results of the study , published by me clearly proves that even when 10 ≤ n ≤50 and p ≤ 0.2, the Poisson distribution can be a good approximation to Binomial distribution.
Hence the answer is Under the Binomial and Poisson distributions gives approximate result is p → 0 n → ∞.
To learn more about Poisson distributions here
https://brainly.com/question/29039650
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