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
Answer:
Step-by-step explanation:
a) (a + b)² = (a + b) * (a +b)
(a + b)³ = (a + b) * (a +b) * (a +b)
a²- b² = (a +b) (a - b)
Here (a + b) is common in all the three expressions
HCF = (a + b)
b) (x - 1) = (x - 1)
x² - 1 = (x - 1) * (x + 1)
(x³ - 1) = (x - 1) (x² + x + 1)
HCF = (x -1)
Start with

Expand both parentheses by multiplying both terms by the number outside:

Sum like terms:

Simplify the "+3" on both sides:

Subtract 2x from both sides:

Divide both sides by 2:

Y = -x - 3 bc the y intercept is -3 and the graph goes down by negative one