Answer:
The probability that a woman in her 60s has breast cancer given that she gets a positive mammogram is 0.0276.
Step-by-step explanation:
Let a set be events that have occurred be denoted as:
S = {A₁, A₂, A₃,..., Aₙ}
The Bayes' theorem states that the conditional probability of an event, say <em>A</em>ₙ given that another event, say <em>X</em> has already occurred is given by:

The disease Breast cancer is being studied among women of age 60s.
Denote the events as follows:
<em>B</em> = a women in their 60s has breast cancer
+ = the mammograms detects the breast cancer
The information provided is:

Compute the value of P (B|+) using the Bayes' theorem as follows:




Thus, the probability that a woman in her 60s has breast cancer given that she gets a positive mammogram is 0.0276.
Answer:
A. 217
Step-by-step explanation:
3,472/16 = 217
Answer:
2
Step-by-step explanation:
Y= 1/10x + 2/10 is what you are left with once the equation is simplified
Answer:
<em>98% of confidence intervals for the Population proportion of people who captured after appearing on the 10 most wanted list</em>
(0.3583 , 0.4579)
Step-by-step explanation:
<u>Explanation</u>:-
<em>Given sample size 'n' = 517</em>
Given data Suppose a sample of 517 suspected criminals is drawn. Of these people, 211 were captured.
'x' =211
<em>The sample proportion</em>


<em>98% of confidence intervals for the Population proportion of people who captured after appearing on the 10 most wanted list</em>


(0.4081-0.0498 , 0.4081 +0.0498)
(0.3583 , 0.4579)
<u><em>Conclusion</em></u>:-
<em>98% of confidence intervals for the Population proportion of people who captured after appearing on the 10 most wanted list</em>
(0.3583 , 0.4579)