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Sagot :
Answer:
0.9091 = 90.91% probability that a person flagged as a future criminal by the Precogs will actually commit a crime
Step-by-step explanation:
Bayes Theorem:
Two events, A and B.
[tex]P(B|A) = \frac{P(B)*P(A|B)}{P(A)}[/tex]
In which P(B|A) is the probability of B happening when A has happened and P(A|B) is the probability of A happening when B has happened.
In this question:
Event A: Flagged as future criminal
Event B: Commits a crime.
In the year 2054 the government estimates that out of every 1,000,100 citizens 1,000,000 will remain law-abiding, and 100 will eventually commit a crime.
This means that [tex]P(B) = \frac{100}{1000100} = 0.00009999[/tex]
If a person is going to commit a crime, the Precogs identify that person correctly 99.999% of the time
This means that [tex]P(A|B) = 0.99999[/tex]
Probability of being identified as a criminal:
0.99999 out of 0.00009999(identified and commits crime).
(1-0.99999) out of (1-0.00009999) (identifed and does not commits crime). So
[tex]P(A) = 0.99999*0.00009999 + (1-0.99999)*(1-0.00009999) = 0.000109988[/tex]
What is the probability that a person flagged as a future criminal by the Precogs will actually commit a crime
[tex]P(B|A) = \frac{P(B)*P(A|B)}{P(A)} = \frac{0.00009999*0.99999}{0.000109988} = 0.9091[/tex]
0.9091 = 90.91% probability that a person flagged as a future criminal by the Precogs will actually commit a crime
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