00:01
Suppose that we have even less knowledge of our patient and we are only given the accuracy of a blood test and prevalence of a disease in our population.
00:09
So we're told that a blood test is 93 % reliable and this means that the test will yield an accurate positive result in 93 % of the cases where the disease is actually present.
00:21
So gestational diabetes affects 4 % of the population in our patient's age group.
00:27
So we have a group that you could have it or you don't have it.
00:35
And 4 % have it, which means 96 % or 0 .96 don't have it.
00:41
And then from there we have accuracy of a test.
00:45
So we could have a positive or a negative result in the test.
00:50
And we're told that the test is 93 % reliable, meaning 93 % of the cases, we get a positive test when they have the disease.
01:00
So 0 .93, which means 7 % of the time we're getting a false reading.
01:10
So with that information, what is the probability? well, before we get to that, let's look at if 100 ,000 people take the blood test, how many people would you expect to test positive and actually have gestational diabetes? so testing positive and having it means that we need to take 0 .04.
01:30
Times .93 and multiply that times 100 ,000 and that's going to be 3 ,720.
01:41
Next we're going to find the probability of having it given that we tested positive.
01:53
So to calculate this, we're going to first find the probability of having it and being positive.
02:02
So that's going to be 0 .04 times 0 .93.
02:06
But then we need to divide that by the probability of a positive result.
02:09
So we can do that if we have it and we test positive, but we can also have that false positive...