[Math] Question about a specific case of the Poisson Distribution.

probability

He everyone! I got the following question in class today, and I was wondering if you can shed some light on the question. Just to clarify, I am not looking for a solution. I am more so looking for a explanation about the problem. Anyway, here is the problem I was given:

A certain typing agency employs 2 typists. The average number of errors per article is 3 when typed by the first typist and 4.2 when typed by the second. If the article is equally likely to be typed by either typist, approximate the probability that it will have no errors.

Here is my solution to the problem:

$E[X] = \sum_{x:p(x)>0} xp(x)$

$\implies E[X] = 3(.5) + 4.2(.5)$

$\implies E[X] = 3.6$

Assuming a Poisson Distribution, we can say the following:

$p(i) = \frac{e^{-\lambda}\lambda^i}{i!}$

$\implies p(0) = \frac{e^{-3.6}(3.6)^0}{0!}$

$\implies p(0) = e^{-3.6}$

However, here is the interesting part. Being quite the perfectionist, I look up all of the answers once I complete the homework. Doing so, I found a similar but different answer which proceeds like this:

$p(0) = p(0|T_1)P(T_1) + p(0|T_2)P(T_2)$

Assuming a Poisson Distribution:

$\implies p(0) = \frac{e^{-3}(3)^0}{0!}(.5) + \frac{e^{-4.2}(4.2)^0}{0!}(.5)$

$\implies p(0) = .5(e^{-3} + e^{-4.2})$

So, which of these are correct? Are they both correct? An explanation would be amazing.

Best Answer

Your second answer is correct. The issue is that an average of Poison processes does not have a rate equal to the average of individual processes. Imagine the limiting case where one typist has a 0 error rate, and other has an infinite error rate. Your first solution would give a zero probability of no errors, but the answer is obviously 50 percent.

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