Modified monty hall problem

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In summary: after the host reveals the other choice is a counterfeit. in summary, the probability of the coin being counterfeit is still 4/5, even after the host reveals the coin is a counterfeit, but the probability of not having taken the counterfeit is 1/5.
  • #1
Dweirdo
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Hello,

I'm sure you are all well familiar with the monty hall problem, so i won't restate it.
there is also a similar problem: the Counterfeit coin problem.
A reminder of the problem:

Assume that you’re presented with three coins, two of them fair and the other a counterfeit that always lands heads. If you randomly pick one of the three coins, the probability that it’s the counterfeit is 1 in 3. This is the prior probability of the hypothesis that the coin is counterfeit. Now after picking the coin, you flip it three times and observe that it lands heads each time. Seeing this new evidence that your chosen coin has landed heads three times in a row, you want to know the revised posterior probability that it is the counterfeit. The answer to this question, found using Bayes’s theorem (calculation mercifully omitted), is 4 in 5. You thus revise your probability estimate of the coin’s being counterfeit upward from 1 in 3 to 4 in 5.

it is easy to show the the probability afterwards is 4 to 5, but then i propose a new problem,
an incest between the monty hall problem and this problem.

suppose after you tossed your coin 3 times, the presenter of the coins tells you that C(one of the coins you didn't choose) is a real coin, and proposes you to know switch to the other coin(coin B, supposing you chose coin A).

Now, it is obvious that you're not supposed to switch, but i had an argument with few mathematicians about the probability of your choice.
In my opinion, the probability that i now hold the counterfeit coin is less than it was before the revelation about coin C. And by baye's theorem i get it's 2\3.

However, whatever reasoning i had for my solution was not convincing as others' reasoning, they said that the probability DOES NOT change:
just like monty hall's where the probability that door A has a car is 1\3, and the other two together is 2\3, and one of them is revealed the other one stays with the 2\3, and your doesn't change.
I can see how this reasoning holds, but my nay's theorem and some intuition that this problem is different when the probabilities in the first place aren't equal, I think I'm right.

Any help with this will be appreciated :)

Thanks!
 
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  • #2
I think you are right that you are not supposed to switch. But I believe the probability of having the counterfeit without switching is still 4/5. Here's my reasoning (although I admit I might be wrong):

As you said, after throwing 3 heads in a row, there's 4/5 chances of having taken the counterfeit. So obviously, there is 1/5 chances of NOT having taken the counterfeit. Thus, there is only 1/5 chance of coin B to be counterfeit (assuming you chose A, and assuming there is only one counterfeit coin among A, B, C). So switching coins would give you only 1/5, which is less than 4/5.

The difference with the Monty Hall problem is that in Monty Hall, you don't get that additional information from throwing the coin three times. The announcer simply opens another door which contains no prize. In that case, you know the probability of door A (your 1st choice) is 1/3, and probability of door B is 2/3 (because there is 2/3 chances for you NOT to have chosen the door with a prize).
 
  • #3
I'm going to assume that, just like in the Monty Hall problem, the host's decision to reveal a non-counterfeit coin is not conditioned on your actions, and that if both remaining coins are real, the one revealed by the host is selected at random.

The probability that you have the counterfeit coin is still 4/5, so you should not switch (assuming the point is to find the counterfeit coin). This is because the host's choice clearly gives us no information (he was going to reveal one of the two coins no matter what).

If you're skeptical, use Bayes' theorem again. Let C be the event that the coin you picked was the counterfeit. Let R be the event that the host reveals one particular coin (choose it in advance) of the two remaining ones. Then suppose event R happens; we want to know P(C|R). This is ##{P(R|C)P(C) \over P(R|C)P(C) + P(R|\overline{C})P(\overline{C})}##. We already agreed that ##P(C) = 0.8## and it is easy to see that ##P(R|C) = P(R|\overline{C}) = 0.5##. We get P(C|R) = 0.8, as claimed.
 
  • #4
Thank you for answering!

i've redone my calculations and you are right, and it can be shown that no matter what is the probability of your first choice, it won't change
 
  • #5


I would approach this problem by first clarifying the assumptions and parameters involved. In the Monty Hall problem, the assumptions are that there are three doors, one of which hides a car and the other two hide goats. The host knows which door hides the car and opens one of the other two doors to reveal a goat. The player is then given the option to switch to the remaining closed door. In this scenario, the player's initial choice has a 1/3 chance of being correct and the remaining door has a 2/3 chance of being correct.

In the modified Monty Hall problem presented, the assumptions are that there are three coins, one of which is counterfeit and always lands heads. The player randomly chooses one of the coins and flips it three times, getting heads each time. The presenter then reveals that one of the remaining coins is not the counterfeit and offers the option to switch to the other remaining coin. The player's initial choice has a 1/3 chance of being the counterfeit and the other remaining coin has a 2/3 chance of being the counterfeit.

In both scenarios, the key factor is the new information provided after the initial choice. In the Monty Hall problem, the new information is the revealed goat, which does not change the probability of the remaining door being the car. In the modified problem, the new information is the revealed non-counterfeit coin, which does change the probability of the remaining coin being the counterfeit. This is because the initial probability of choosing the counterfeit coin was 1/3, but after seeing three heads in a row, the probability of the chosen coin being the counterfeit increases to 4/5 (as calculated using Bayes's theorem). Therefore, the probability of the remaining coin being the counterfeit decreases to 1/5.

In conclusion, I believe that the modified Monty Hall problem is different from the original problem and that the player should switch to the remaining coin, as the probability of it being the counterfeit is now 1/5 rather than 2/3. However, it is important to note that this solution is based on the assumptions and parameters given in the problem and may change if they are altered.
 

1. What is the modified Monty Hall problem?

The modified Monty Hall problem is a variation of the classic Monty Hall problem, which is a famous probability puzzle. In this version, instead of three doors, there are four doors, and instead of one door being revealed by the host, two doors are revealed. The contestant must choose one door to open and try to find the prize behind it.

2. How is the modified Monty Hall problem different from the original?

The main difference is that there are four doors instead of three and two doors are revealed instead of one. This changes the probabilities and strategies involved in the game.

3. What are the probabilities of winning in the modified Monty Hall problem?

The probability of winning by switching doors is 2/3, while the probability of winning by sticking with the original choice is 1/3. This is different from the original Monty Hall problem, where the probabilities were 1/3 and 2/3 respectively.

4. How do you solve the modified Monty Hall problem?

To solve the modified Monty Hall problem, you can use the same strategy as the original problem. That is, always switch doors after the host reveals two doors. This will give you a higher chance of winning in the long run.

5. Why is the modified Monty Hall problem important?

The modified Monty Hall problem is important because it challenges our intuition and understanding of probabilities. It also demonstrates the concept of conditional probability, where the probability of an event changes based on new information. This can be applied to real-life situations and decision-making processes.

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