Assume a test for cancer correctly identifies 98% of the people tested who do have cancer. Unfortunately, the test gives a false positive reading 1.5% of the time. (A false positive is when the test says you have cancer, but you actually do not.) Millions of people are tested and 0.6% actually have cancer. Find the probability that a person with a positive test result has cancer

0.2828.

Step-by-step explanation:

From the information given:

Therefore: P(No Cancer)=1-P(Cancer)=1-0.006=0.994

We want to determine the probability that a person with a positive test result has cancer. i,e. P(Cancer|Positive)

Using Bayes Theorem for Conditional Probability

Therefore, the probability that a person with a positive test result has cancer is 0.2828.

yes

step-by-step explanation:

yes

2(2x + 3) = -4 + 2(2x + 5)

4x + 6 = -4 + 4x + 10

4x + 6 = 4x + 6

4x - 6 + 6 = 4x - 6 + 6

4x = 4x

x = x

unlimited solutions.