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

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Discussion Overview

The discussion revolves around a probability problem involving a box containing 120 balls, of which a random variable X represents the number of white balls. Participants explore the probability of drawing a white ball first, given that the expected value of X is 30. The conversation touches on concepts of expected values, indicator random variables, and the implications of sampling with replacement.

Discussion Character

  • Exploratory
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant presents the problem and notes the official answer as E[X]/120 = 1/4, questioning the reasoning behind it.
  • Another participant suggests reviewing the properties of expected values, specifically E[aX] = aE[X].
  • A participant expresses familiarity with expected value properties but struggles to connect them to the problem's solution, indicating confusion about the equation E[X] = 120p.
  • One participant mentions receiving advice from another forum to define an indicator random variable X_i, which clarifies their understanding of the solution.
  • A later reply proposes a method to find P(First ball is white | X = x) and suggests that the information about Y and the sample size may not be necessary for solving the initial question.

Areas of Agreement / Disagreement

Participants express varying levels of understanding regarding the problem and its solution. While some find clarity through discussions about expected values and indicator variables, others remain uncertain about the relevance of certain aspects of the problem, indicating a lack of consensus on the best approach to the question.

Contextual Notes

Participants highlight potential ambiguities in the problem's wording and the necessity of certain conditions, such as the relevance of k and Y in determining the probability of the first ball being white.

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?
 
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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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