Probability question; Conditional probability and poisson distribution

AI Thread Summary
The discussion revolves around calculating the conditional probability p(Y = r|X = k) in a scenario involving a Poisson process for radioactive particle emissions. The user correctly identifies that p(Y = r|X = k) can be expressed as p((Y = r) ∩ (X = k)) / p(X = k) and recalls the Poisson distribution formula for p(X = k). However, confusion arises in determining p((Y = r) ∩ (X = k)), leading to an incorrect application of the binomial distribution. Clarifications indicate that while the user's approach is relevant, it does not represent the joint probability needed for the conditional calculation. The conversation emphasizes the need to accurately connect the Poisson and binomial distributions in this context.
TaliskerBA
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Homework Statement



A radioactive source emits particles according to a Poisson process, at an average rate of λ per unit time. Each particle emitted has probability p of being detected by an instrument, independently of other particles. Let X be the number of particlese emitted in a given time interval of length T , and Y the number of those particles that are detected. As usual, let μ = λT and q = 1 − p.
(i) What is the conditional probability p(Y = r|X = k)?


Homework Equations



I know that I want p(Y=r|X = k) = p((Y=r) ∩ (X=k)) / p(X=k)

I know from poisson distribution that p(X=k) = ((μ^k)/k!)*e^(−μ)


The Attempt at a Solution



I don't understand how I can work out what p((Y=r) ∩ (X=k)) equals but this is my attempted solution:

Since there are k particles emitted and we want to know the probability that r of them have been detected then using binomial distribution:

p((Y=r) ∩ (X=k)) = [k choose r](p^r)(q^(k-r))

I know this is wrong but I can't quite work out how to tie it all together...
 
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TaliskerBA said:
Since there are k particles emitted and we want to know the probability that r of them have been detected then using binomial distribution:

p((Y=r) ∩ (X=k)) = [k choose r](p^r)(q^(k-r))

I know this is wrong but I can't quite work out how to tie it all together...

You wrote down a formula assuming that k particles have been emitted. Therefore this is not the joint probability, but it is still relevant to the conditional probability that you want to compute...
 
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