Probability with conditional replacement

In summary, we have a bag with n balls, half of which are green and half of which are blue. In an experiment where we randomly remove two balls and either put them back in the bag or on the ground depending on their type, the probability of putting the balls on the ground is n/2(n-1). The expected number of times this experiment must be repeated until a ball is put on the ground is 2(n-1)/n. The expected number of times the experiment must be repeated before the bag is empty is n/2(n-1).
  • #1
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Homework Statement


We have a bag of n balls, n/2 of which are green and n/2 of which are blue. Consider the following experiment: We reach into the bag and pull out two balls. If they of the same type, we put them both back in the bag. If they are of di erent types we put them both on the ground.
1. What is the probability that we put the balls on the ground?
2. What is the expected number of times we have to repeat this experiment until we get to put some ball on the ground?
3. What is the expected number of times we have to repeat this experiment before the bag is empty?


Homework Equations





The Attempt at a Solution


1. n/2n * n/2(n-1) + n/2n * n/2(n-1) = n/2(n-1)
2. 2(n-1)/n
 
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  • #2
OK on the first two parts. For the third part, is there any reason that the expected times wouldn't be additive? I mean, whether it takes 10 tries or 1 try to remove balls n and n-1, the number of tries it will take after that to remove n-2 and n-3 should be the same.

So you can write out the sum and fiddle it down to a formula.
 

FAQ: Probability with conditional replacement

1. What is conditional replacement in probability?

Conditional replacement in probability is a concept that involves adjusting the probability of an event occurring based on additional information. It takes into account the occurrence of a previous event and updates the probability of a subsequent event accordingly.

2. How is conditional replacement different from regular probability?

Regular probability deals with the likelihood of an event occurring without considering any additional information. On the other hand, conditional replacement takes into account previous events and updates the probability of future events based on that information.

3. What are some real-life examples of conditional replacement in probability?

One example of conditional replacement in probability is when predicting the outcome of a sports game. The probability of a team winning may change if one of their star players gets injured during the game. Another example is in medical testing, where the probability of a patient having a certain disease may change based on their medical history.

4. How is conditional replacement calculated in probability?

Conditional replacement is calculated using conditional probability, which is the probability of an event occurring given that another event has already occurred. It can be calculated using the formula P(A|B) = P(A and B) / P(B), where A is the event of interest and B is the event that has already occurred.

5. What are the limitations of conditional replacement in probability?

One limitation of conditional replacement in probability is that it relies on the assumption that the events are independent of each other. This may not always be the case in real-life situations. Additionally, the accuracy of conditional replacement can be affected by the quality and quantity of the additional information being considered.

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