Answer:
39.17% probability that a woman in her 60s who has a positive test actually has breast cancer
Explanation:
Bayes Theorem:
Two events, A and B.
![P(B|A) = (P(B)*P(A|B))/(P(A))](https://img.qammunity.org/2021/formulas/mathematics/college/dpl2om35c6759cj1w3kaim008n3d4pjd3q.png)
In which P(B|A) is the probability of B happening when A has happened and P(A|B) is the probability of A happening when B has happened.
In this question:
Event A: Positive test.
Event B: Having breast cancer.
3.65% of women in their 60s get breast cancer
This means that
![P(B) = 0.0365](https://img.qammunity.org/2021/formulas/mathematics/college/weoi867694yyl2hv58ae2ciqvruifwkl6v.png)
A mammogram can typically identify correctly 85% of cancer cases
This means that
![P(A|B) = 0.85](https://img.qammunity.org/2021/formulas/mathematics/college/l89k9zx46y8hnud5xmyihbvsg9xedy4akm.png)
Probability of a positive test.
85% of 3.65% and 100-95 = 5% of 100-3.65 = 96.35%. So
![P(A) = 0.85*0.0365 + 0.05*0.9635 = 0.0792](https://img.qammunity.org/2021/formulas/mathematics/college/4q135yopxlooj1dsbcjfvwhgnv89ov4gvu.png)
What is the probability that a woman in her 60s who has a positive test actually has breast cancer?
![P(B|A) = (0.0365*0.85)/(0.0792) = 0.3917](https://img.qammunity.org/2021/formulas/mathematics/college/7s4snboqqq89yson3vh8l6oym4hpx75tfy.png)
39.17% probability that a woman in her 60s who has a positive test actually has breast cancer