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.

no, the equation would be invalid since they are both not equal.

step-by-step explanation:

here you got

4y-6+4y 2-9

first, you would simplify the equation on the form.

4y-6+4y 2-9

then, move all the terms that contains a y to the left and all the other terms to the right.

+4y-4y+-9-6

finally, you will simplify the left and the right side of the equation.

y=-3