Independent solution

How to solve this Bayes' Theorem question

Setup

Setup

Let F identify a female employee and C identify plan contribution.

Pr(F)=0.45,Pr(Fc)=0.55\Pr(F)=0.45,\qquad \Pr(F^c)=0.55

Model

Model

Weight each category-specific contribution rate by its employee share.

Pr(FC)=0.45(0.20)=0.09\Pr(F\cap C)=0.45(0.20)=0.09
Pr(FcC)=0.55(0.30)=0.165\Pr(F^c\cap C)=0.55(0.30)=0.165

Compute

Compute

Normalize the female-contributor mass over all contributors.

Pr(FC)=0.090.09+0.165\Pr(F\mid C)=\frac{0.09}{0.09+0.165}
=617=0.3529411765=\frac6{17}=0.3529411765

Answer

Answer

The conditional probability rounds to 0.35.

0.35(C)\boxed{0.35\quad\text{(C)}}