Independent solution

How to solve this Conditional Probability question

Setup

Setup

The middle age group has the remaining prior probability after subtracting the two supplied extreme-group shares.

Pr(M)=10.550.15=0.30\Pr(M)=1-0.55-0.15=0.30
Pr(U)=0.55,Pr(O)=0.15\Pr(U)=0.55,\qquad \Pr(O)=0.15

Model

Model

Weight each group's suburban likelihood by its prior, then normalize the target group's joint weight.

Pr(S)=g{U,M,O}Pr(g)Pr(Sg)\Pr(S)=\sum_{g\in\{U,M,O\}}\Pr(g)\Pr(S\mid g)
Pr(US)=Pr(U)Pr(SU)Pr(S)\Pr(U\mid S)=\frac{\Pr(U)\Pr(S\mid U)}{\Pr(S)}

Compute

Compute

Evaluate the three compatible joint weights and their Bayes ratio.

Pr(S)=0.55(0.20)+0.30(0.60)+0.15(0.35)=0.3425\Pr(S)=0.55(0.20)+0.30(0.60)+0.15(0.35)=0.3425
Pr(US)=0.55(0.20)=0.1100\Pr(U\cap S)=0.55(0.20)=0.1100
Pr(US)=0.11000.3425=44137=0.321167\Pr(U\mid S)=\frac{0.1100}{0.3425}=\frac{44}{137}=0.321167\ldots

Answer

Answer

The requested conditional probability rounds to 0.32.

0.32(C)\boxed{0.32\quad\text{(C)}}