What is the Probability Distribution Function for Total Rotten Fruit?

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Discussion Overview

The discussion revolves around determining the probability distribution function (pdf) for the total number of rotten fruits, specifically apples and oranges, given their individual probabilities of rotting. Participants explore the mathematical formulation of this problem, including the expectation of rotten fruits and the implications of combining different probability distributions.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant describes the problem of finding the pdf for total rotten fruits as potentially involving a product of two binomial distributions, but notes the need to consider all combinations of rotten fruits.
  • Another participant provides a formula for the probability that a specific number of fruits will rot, expressed as a sum of terms involving probabilities of apples and oranges.
  • A different participant mentions having derived the pdf using two binomial distributions but expresses difficulty in simplifying the expectation.
  • One participant references a mathematical identity related to polynomial division, suggesting its relevance to the discussion.
  • Another participant outlines a specific case for two fruits, detailing the probabilities for different combinations of rotten apples and oranges, and presents a formula for the probability of z rotten fruits based on binomial coefficients.
  • A later reply summarizes the findings in a more concise form, relating the probability of rotten fruits to a binomial expansion and simplifying the expression.

Areas of Agreement / Disagreement

Participants express varying approaches to the problem, with no consensus reached on a single method or formula for the pdf. Different interpretations of the probability distributions and their combinations are presented, indicating ongoing debate.

Contextual Notes

Some participants acknowledge errors in their initial posts, indicating that assumptions or calculations may be incomplete or incorrect. The discussion reflects a complexity in deriving the expectation from the pdf, with unresolved mathematical steps and dependencies on the definitions of the probabilities involved.

ouiouiwewe
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Hi guys,

Here's a description of the problem:

Suppose we have x apples and y oranges where each apple has a probability pa to rot and each orange has a probability po to rot, then what's the pdf of the total number of fruit z being rotten.

This pdf looks like a product of two binomial distributions on the surface. However, since z = x+y, x >= 0, y >= 0, then it is actually necessary to sum over all combinations of scenarios (i.e. 6 fruit rotten = 3 apples rotten + 3 oranges rotten or 6 fruits rotten = 1 apple rotten + 5 oranges rotten).

By intuition, I worked out the expectation to be x*pa + y *po and it appears to be correct when I manually tested my problem on a spreadsheet. However, I am not quite sure how that expectation can be derived from this messy pdf.

Any suggestions?

Thanks.
 
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The probability that z fruits will rot, is P(A)^0·P(O)^z+P(A)^1·P(O)^(z-1)+P(A)^2·P(O)^(z-2)+...+P(A)^z·P(O)^0

You could also write that as:
[tex]\sum^{z}_{k=0}P(A)^kP(O)^{z-k}[/tex]
 
Last edited:
This is close to the derivation I had, but instead of P(A)^[something] and P(O)^[something], I had two different binomial distributions. I have no problem getting the pdf, but I have trouble simplifying the expectation.
 
Are you familiar with this division?
[tex](a^n-b^n):(a-b)=a^{n-1}+a^{n-2}b+a^{n-3}b^2+\ldots+b^{n-1}[/tex]
 
I saw this sum in the derivation of the binomial expectation. Anyhow, this is what I have for the probability of having 2 rotten fruits:

prob of having 2 rotten apples * prob of having 0 rotten oranges
+
prob of having 1 rotten apple * prob of having 1 rotten orange
+
prob of having 0 rotten apples * prob of having 2 rotten oranges

This seems to be the product of two binomial distributions and then summed over all possible combinations.
 
(Ignore my first post, there are errors in it.)

Let's say you have 2 fruits. Then:
-Both fruits can be apples. The probability for those being rotten is P(A)2
-Fruit 1 can be apple, fruit 2 can be orange. The probability for those being rotten is P(A)·P(O)
-Fruit 1 can be orange, fruit 2 can be apple. The probability for those being rotten is P(A)·P(O)
-Both fruits can be oranges. The probability for those being rotten is P(O)2

Since we don't know how many fruits we have, the probability that both the fruits will rot, is the average of the probabilities above, which is:
(P(A)2+2 P(A)·P(O)+P(O)2)/4

The probability that z fruits will be rotten is:
[tex]\frac{\binom{z}{0}P(A)^zP(O)^0+\binom{z}{1}P(A)^{z-1}P(O)^1+\binom{z}{2}P(A)^{z-2}P(O)^2+\ldots+\binom{z}{z}P(A)^0P(O)^z}{2^z}[/tex]

This is exactly the same, but said in a shorter way:
[tex]\frac{\sum^{z}_{k=0}\binom{z}{k}P(A)^{z-k}P(O)^k}{2^z}[/tex]

By using this equation: [tex](a+b)^n=\binom{n}{0}a^nb^0+\binom{n}{1}a^{n-1}b^1+\binom{n}{2}a^{n-2}b^2+\ldots+\binom{n}{n}a^0b^n[/tex]

We get that:
[tex]\frac{\sum^{z}_{k=0}\binom{z}{k}P(A)^{z-k}P(O)^k}{2^z}=\frac{(P(A)+P(O))^z}{2^z}=\left(\frac{P(A)+P(O)}{2}\right)^z[/tex]
 

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