I Probability of White Ball in Box of 120 Balls: Solved!

CGandC
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Problem:
In a box there are ##120## balls with ## X ## of them being white and ## 120 - X ## being red for random variable ##X##.
We know that ## E[ X] = 30 ##. We are taking out ## k ## balls randomly and with returning ( we return each ball we take out, so there is equal probability for each ball every time we take out a ball ), for ## k \geq 2 ##.
Let ## Y ## be the number of white balls in the sample that was taken out.
What is the probability of the first ball being white?

Note: This was the first question of an old exam and there were more questions that were based on it in the exam later on ( so it might be the case that we don't need to use ## k ## here. ), none of them helped in inferring the reasoning for the answer to this problem.

The official answer was:
## E[ \frac{X}{120}] = \frac{1}{4} ##, hence the probability of the first ball being white is ## \frac{1}{4} ##

Question:
I tried different things, among them being attempting to use binomial ,negative-binomial, hyper-geometric distributions in the problem, but I kept getting stuck because I don't know what ## X ## is since it is a random variable.
Then I tried getting ahead with the following equations:
## E[ X] = \sum_{i=1}^{120} x P(X = x) ## , ## E[ X] = \sum_{i=1}^{120} P(X \geq i) ## , but I was unable to proceed.

Do you have any explanation for the answer? I'm unable to retrace the steps necessary to arrive to it so I can't figure out how to arrive at the answer.

Thanks in advance for any help!
 
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You should review the basic properties of expected values. What is the expected value of ##aX##, where ##a## is a constant real number?
 
FactChecker said:
You should review the basic properties of expected values. What is the expected value of ##aX##, where ##a## is a constant real number?
## E[ aX] = aE[ X] ##, I'm familiar with the basic properties of expected value butthese don't give a clue to why the answer is as is. All I can understand from this is that ## E[X] = 120 \cdot p ## where p is the wanted probability, but there I don't understand the reasoning for why the sum on the right-hand side of the equation is as is.

Edit: I've asked this question on mathexchange and I was told to define an indicator random variable ## X_i ## which says " the value of ## X ## is ## i ## " and then to use linearity of expectation ## E[ X]=\sum E[X_i] ##. Now I understand the solution, though the question itself was misleading and confusing.

Thanks for the help!
 
Last edited:
CGandC said:
## E[ aX] = aE[ X] ##, I'm familiar with the basic properties of expected value butthese don't give a clue to why the answer is as is. All I can understand from this is that ## E[X] = 120 \cdot p ## where p is the wanted probability, but there I don't understand the reasoning for why the sum on the right-hand side of the equation is as is.

Edit: I've asked this question on mathexchange and I was told to define an indicator random variable ## X_i ## which says " the value of ## X ## is ## i ## " and then to use linearity of expectation ## E[ X]=\sum E[X_i] ##. Now I understand the solution, though the question itself was misleading and confusing.

Thanks for the help!
First think about finding P(First ball is white | X = x] : this will be an expression that involves x, call it [for my illustration] f(x)

Then P(First ball is white) = E[First ball is white | [X = x]] = E(f(x))

This should lead you through it and see where the information about E(X) is useful.

finally: this is [in my opinion] a crappily worded question: You're told that k >=2 balls will be selected and Y is the number of white balls in the sample, but nothing about that is needed for solving the problem about P(First ball is white). I see no reason the business about Y and the sample needs to be in this question
 
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