Calculating Probability in a Lying Society: Truth-Telling on a Mysterious Island

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In summary, the inhabitants of the island tell the truth 1/3 of the time and lie 2/3 of the time. On occasion, one person made a statement and the person after him said the statement was true. The probability that the statement is actually true is 1/5. This can be determined by considering the four possible scenarios and using Bayes' theorem to calculate the probability of the statement being true in each scenario.
  • #1
Jin314159
It is known that the inhabitants of an island tell the truth 1/3 of the time and lie 2/3 of the time. On an occasion, one person made a statement and the person after him said the statement was true. What is the probability that the statement is actually true?
 
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  • #2
I would think 1/9 but i don't actually remember how to do probablility. :wink:
 
  • #3
Consider the 4 possibilities -
1st person truthful, 2nd person truthful
1st person truthful, 2nd person lying
1st person lying, second person truthful
1st person lying, second person lying.

Work out how probable each possibility is, then work out which possibilities actually result in the second person claiming the first person is truthful. The rest should be easy.

Claude.
 
  • #4
Here's what I did:

P (1st telling truth | second says first is telling truth) =
P (1st telling truth and second says first is telling truth) / [P(1st is telling truth and second says first is telling truth) + P(1st is lying and second says first is selling truth)]
= 1/3
 
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  • #5
Jin314159 said:
It is known that the inhabitants of an island tell the truth 1/3 of the time and lie 2/3 of the time. On an occasion, one person made a statement and the person after him said the statement was true. What is the probability that the statement is actually true?

Or they are telling true , or they are lying .

The answer is ( 1/3 * 1/3 ) / ( 1/3 * 1/3 + 2/3 * 2/3 ) = 1/5 .
 
  • #6
The answer is 1/3. A good way to see this is to do what Claude Bile suggested. Look at the four different "possibilities" one at a time. But you should also ask yourself if they're all really possible. (Big hint: They're not).
 
  • #7
I can not say something truthful, and then have my neighbor say something truthful also? there's a 1/3 chance that i would say something truthful, and a 1/3 chance that my neighbor would say something truthful... no?
 
  • #8
Suppose that you say "it's raining", and your neighbor says "what musky ox is saying is true".

Which ones of the following alternatives are possible, and which ones aren't?

1. You're telling the truth and he's telling the truth.
2. You're telling the truth and he's lying.
3. You're lying and he's telling the truth.
4. You're lying and he's lying.

Once you have figured that out, the rest will be very easy.
 
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  • #9
Fredrik said:
The answer is 1/3. A good way to see this is to do what Claude Bile suggested. Look at the four different "possibilities" one at a time. But you should also ask yourself if they're all really possible. (Big hint: They're not).

The answer is not 1/3 . Let's follow the Claude's suggestion:

Claude Bile said:
Consider the 4 possibilities -
1st person truthful, 2nd person truthful
1st person truthful, 2nd person lying
1st person lying, second person truthful
1st person lying, second person lying.


The first pair of persons ocurrs with probability: 1/3 * 1/3 = 1/9
The second pair ocurrs with probability: 1/3 * 2/3 = 2/9
The third pair ocurrs with probability: 2/3 * 1/3 = 2/9
The fourth pair ocurrs with probability: 2/3 * 2/3 = 4/9

But, since the 2 persons agreed, we know only the first or the last case can be possible.
So, the probability we have a truthful pair of persons is (1/9) / (1/9 + 4/9) = 1/5.

This is classical Bayes. :smile:
 
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  • #10
Rogerio said:
The answer is not 1/3 .
...
But, since the 2 persons agreed, we know only the first or the last case can be possible.
So, the probability we have a truthful pair of persons is (1/9) / (1/9 + 4/9) = 1/5.

This is classical Bayes. :smile:
Yes, you're right. I assigned probability 0 to the impossible "possibilities", but that's not the right way to do this. :redface:
 
  • #11
Well, in fact, you and Claude Bile did the job !

I just followed yours suggestion... :smile:
 

FAQ: Calculating Probability in a Lying Society: Truth-Telling on a Mysterious Island

1. How do you calculate probability in a lying society?

Calculating probability in a lying society involves taking into account the likelihood of deception and manipulations in the data. This can be done by considering the credibility of the source and the context in which the information was obtained.

2. What factors should be considered when determining truth-telling in a mysterious island?

When determining truth-telling in a mysterious island, factors such as the motives of the individuals, their past behavior, and the consequences of their statements should be considered. It is also important to assess the reliability of the evidence presented.

3. How can the reliability of data be determined in a lying society?

The reliability of data in a lying society can be determined by cross-checking information from multiple sources, verifying the accuracy of the data through experiments or observations, and considering the credibility and biases of the sources.

4. Is it possible to accurately calculate probability in a society where lying is common?

While it may be challenging, it is still possible to accurately calculate probability in a society where lying is common. By carefully examining the available evidence and taking into account the prevalence of deception, accurate probabilities can still be determined.

5. How can probability calculations be used to determine the truth in a mysterious island scenario?

Probability calculations can be used to determine the truth in a mysterious island scenario by weighing the likelihood of different outcomes and evaluating the credibility of the information presented. By considering all the available data and assessing the probability of each scenario, the truth can be determined with a higher degree of accuracy.

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