A manufacturing process produces integrated circuit chips. Over the long run the fraction of bad chips produced by the process is around 20%. Thoroughly testing a chip to determine whether it is good or bad is rather expensive, so a cheap test is tried. All good chips will pass the cheap test, but so will 10% of the bad chips.
Given that a chip passes the test, what is the probability that the chip was defective?

0.0244 (2.44%)

Step-by-step explanation:

defining the event T= the chips passes the tests , then

P(T)= probability that the chip is not defective * probability that it passes the test given that is not defective  + probability that the chip is defective * probability that it passes the test given that is defective = 0.80 * 1 + 0.20 * 0.10 = 0.82

for conditional probability we can use the theorem of Bayes. If we define the event D=the chip was defective , then

P(D/T)=P(D∩T)/P(T) = 0.20 * 0.10/0.82=  0.0244 (2.44%)

where

P(D∩T)=probability that the chip is defective and passes the test

P(D/T)=probability that the chip is defective given that it passes the test

the two may have that, even a breakdown is probably offered

step-by-step explanation:

first you will have to convert 3/4 into a decimal

which is .75

then you will have to divide 1.5 by .75

which is 2

no you have to divide