Answer:
B) μD = 0.60 ± 0.10(1.397)
Step-by-step explanation:
The confidence interval is given by:

Where
MD=60
n=9
df=n-1=8


Then the confidence interval is
μD=0.60±1.397*(0.3/√9)
μD=0.60±0.10*(1.397)
The question we need to ask is what percent of 2 is 40?
40 is 20 times 2 so 20 would be 2,000%
We need to subract 100% from any percent change:
2,000% - 100% = 1,900%
ANSWER: 1,900%
Answer:
39.17% probability that a woman in her 60s who has a positive test actually has breast cancer
Step-by-step explanation:
Bayes Theorem:
Two events, A and B.

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 
A mammogram can typically identify correctly 85% of cancer cases
This means that 
Probability of a positive test.
85% of 3.65% and 100-95 = 5% of 100-3.65 = 96.35%. So

What is the probability that a woman in her 60s who has a positive test actually has breast cancer?

39.17% probability that a woman in her 60s who has a positive test actually has breast cancer