(3) In a certain factory, machines D, E and F all produce computer chips the same type. Of their production, machines D, E and F, respectively produce 2%, and 1% defective chips. Machine D produces 30% of the output of the factory, machi E 25% and machine F the rest. Suppose one chip is selected at random from the output of the factory and the chip defective (a) Use Bayes' theorem to find the probabilities that the chip was manufactured machines D, E and F. (b) Identify the data, hypotheses, likelihoods, prior probabilities and posterior prob bilities. (c) Redo the computation of (a) using a Bayesian updating table.
(3) In a certain factory, machines D, E and F all produce computer chips the same type. Of their production, machines D, E and F, respectively produce 2%, and 1% defective chips. Machine D produces 30% of the output of the factory, machi E 25% and machine F the rest. Suppose one chip is selected at random from the output of the factory and the chip defective (a) Use Bayes' theorem to find the probabilities that the chip was manufactured machines D, E and F. (b) Identify the data, hypotheses, likelihoods, prior probabilities and posterior prob bilities. (c) Redo the computation of (a) using a Bayesian updating table.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:(3)
In a certain factory, machines D, E and F all produce computer chips of
the same type. Of their production, machines D, E and F, respectively produce 2%, 3%
and 1% defective chips. Machine D produces 30% of the output of the factory, machine
E 25% and machine F the rest.
Suppose one chip is selected at random from the output of the factory and the chip is
defective
(a) Use Bayes' theorem to find the probabilities that the chip was manufactured on
machines D, E and F.
(b) Identify the data, hypotheses, likelihoods, prior probabilities and posterior proba-
bilities.
(c) Redo the computation of (a) using a Bayesian updating table.
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