Murder case Conditional probability

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Discussion Overview

The discussion revolves around a conditional probability problem related to a murder case involving a lie detector test. Participants explore the expected outcomes of the test, the implications of test results on the probability of guilt, and considerations for improving the lie detector's effectiveness. The scope includes theoretical reasoning and mathematical calculations.

Discussion Character

  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant outlines the scenario involving a murder case and the use of a lie detector test, specifying the probabilities of true and false results.
  • Another participant attempts to derive the probability of the murderer being identified given a positive test result, but expresses confusion over the calculations, suggesting a factor of N is missing.
  • A different participant corrects the previous claim, arguing that the calculation of the probability of a positive test result must include the division by N, and provides reasoning for this adjustment.
  • One participant reiterates the initial scenario and details the probabilities associated with true positives and false positives, suggesting these probabilities are crucial for solving related questions.

Areas of Agreement / Disagreement

Participants express differing views on the correct approach to calculating probabilities, with some asserting the need for adjustments in the formulas used. There is no consensus on the correct method or final outcomes, indicating ongoing debate.

Contextual Notes

Participants highlight the importance of understanding the probabilities involved, including true positive and false positive rates, but do not resolve the discrepancies in their calculations or assumptions.

dede4metal
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Guys my question should be easy but I cannot understand how it works, here is how it goes.

A murder case involves the death of a guest at a large party in a country house. The police are certain that there is only one murderer who is among the N = 100 remaining people in the house. However, they have no evidence at all so that they suspect everyone equally. They decide to use a lie detector test on everyone. Only the murderer lies. If an interviewee lies during the test, the lie detector will return a positive result (i.e. correctly identify the interviewee as a liar) with a probability of p = 80%. However, the lie detector also has a q = 5% chance of incorrectly identifying an honest interviewee as a liar.
(a) How many people are expected to fail the lie detector test?
(b) Mickey is the first to be interviewed. He fails the test. Show that the probability that Professor Plum is guilty is given by p/[p+(N−1)q]. Evaluate this quantity using the parameters given.
(c) One can attempt to design a more discriminating lie detector. What should be the condition for the ratio q/p if the goal is a probability of at least 75% that an interviewee is guilty if he/she fails the test. Comment on whether it is more important to improve the parameter p, q or both.

cheers!
 
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WHAT I GET IS P(positive)=p+q(N-1)

P(murderer given positive)/P(positive given murderer)=P(meruderer)/P(positive)

but this gives me P(murderer given positive)=p/[N[p+(N−1)q]] therefore an extra factor of N!
 
dede4metal said:
WHAT I GET IS P(positive)=p+q(N-1)

This is wrong. you have to divide by N here. someone gets a positive test if
(they are the murderer (prob. 1/N) AND they then test positive (prob p). OR
(they are not the murderer (prob. (N-1)/N and they test positive (prob q.)
 
dede4metal said:
Guys my question should be easy but I cannot understand how it works, here is how it goes.

A murder case involves the death of a guest at a large party in a country house. The police are certain that there is only one murderer who is among the N = 100 remaining people in the house. However, they have no evidence at all so that they suspect everyone equally. They decide to use a lie detector test on everyone. Only the murderer lies. If an interviewee lies during the test, the lie detector will return a positive result (i.e. correctly identify the interviewee as a liar) with a probability of p = 80%. However, the lie detector also has a q = 5% chance of incorrectly identifying an honest interviewee as a liar.
(a) How many people are expected to fail the lie detector test?
(b) Mickey is the first to be interviewed. He fails the test. Show that the probability that Professor Plum is guilty is given by p/[p+(N−1)q]. Evaluate this quantity using the parameters given.
(c) One can attempt to design a more discriminating lie detector. What should be the condition for the ratio q/p if the goal is a probability of at least 75% that an interviewee is guilty if he/she fails the test. Comment on whether it is more important to improve the parameter p, q or both.

cheers!

The true positive probability is 0.8 and the false negative probability is 1 - 0.8 = 0.2 given you are guilty (P=0.01)

The true negative probability is 0.95 and the false positive probability is 1 - .95 = 0.05 given that you are innocent (P=0.99).

This is all you need to solve for the probability of finding the guilty person after k tests (or any related question). Note the probability of a false positive: (0.05)(.99)= 0.0495 is much larger than a true positive: (0.8)(.01)= 0.008
 
Last edited:

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