Answer:
DE
Step-by-step explanation:
See how DE cuts through half? We shouldn't be too accurate for the midsegment.
Complete Question
Suppose there was a cancer diagnostic test was 95% accurate both on those that do and 90% on those do not have the disease. If 0.4% of the population have cancer, compute the probability that a particular individual has cancer, given that the test indicates he or she has cancer.
Answer:
The probability is 
Step-by-step explanation:
From the question we are told that
The probability that the test was accurate given that the person has cancer is

The probability that the test was accurate given that the person do not have cancer is

The probability that a person has cancer is

Generally the probability that a person do not have cancer is

=> 
=> 
Generally the probability that a particular individual has cancer, given that the test indicates he or she has cancer is according to Bayes's theorem evaluated as

=> 
=> 
As you increase the subintervals the area will be closer and closer to the real value. In other words your approximation gets better.
As you increase the intervals, there will be more rectanagles and the added area of these rectangles are converging towards the actual area under the curve.
Answer:
y = -3x + 3
Step-by-step explanation:
Slope = -3
y-intercept = 3
Substitute values into slope intercept form :
y=mx + b
Where :
m= Slope
b = y-intercept
