Independent solution

How to solve this Bayes' Theorem question

Setup

Setup

Let D denote a defective item and T a positive test indication. Convert the stated accuracy on nondefective items into a false-positive probability.

Pr(D)=0.10,Pr(TD)=0.80\Pr(D)=0.10,\qquad \Pr(T\mid D)=0.80
Pr(TDc)=10.40=0.60\Pr(T\mid D^c)=1-0.40=0.60

Model

Model

Partition the positive-test event by the item's true condition and apply Bayes' formula.

Pr(DT)=Pr(TD)Pr(D)Pr(TD)Pr(D)+Pr(TDc)Pr(Dc)\Pr(D\mid T)=\frac{\Pr(T\mid D)\Pr(D)}{\Pr(T\mid D)\Pr(D)+\Pr(T\mid D^c)\Pr(D^c)}

Compute

Compute

Insert the prior and the two conditional indication probabilities.

Pr(DT)=(0.80)(0.10)(0.80)(0.10)+(0.60)(0.90)\Pr(D\mid T)=\frac{(0.80)(0.10)}{(0.80)(0.10)+(0.60)(0.90)}
Pr(DT)=0.080.62=431=0.1290322581\Pr(D\mid T)=\frac{0.08}{0.62}=\frac{4}{31}=0.1290322581

Answer

Answer

The posterior defective probability is 4/31.

431(D)\boxed{\frac{4}{31}\quad\text{(D)}}