"Imagine there is some rare disease that only affects 1 in 10,000 people, but if you get it, it's completely fatal and there is no cure, death is guaranteed. One day you get really paranoid and decide to take a test to see if you have the disease or not, so you go down to your local doctor and he says there's a simple test you can take which is 99% accurate in its diagnosis. So you take the test, then go home and wait. A couple weeks later a letter from the clinic comes through your door and you open it and it says the dreaded words "You have the disease" - so naturally, you would completely freak out, right? However, if you think about it, despite receiving this letter, you still have less than a 1% chance of actually having the disease. Even tho the test is 99% accurate and affects just 1 in 10,000 people." When I first heard this I couldn't believe it, but after much contemplation it is most definitely true. Imagine if we take a sample size of 1,000,000 people. As 1 in 10,000 get the disease, this means 100 from our sample size of 1m would have the disease. Of these 100 people, 99 would be correctly diagnosed as having the disease and 1 would be incorrectly told that they don't have the disease. There would be 999,900 remaining people who do not have the disease. However, as the test is only 99% accurate, 1% of these 999,900 (i.e. 9,999 people) would receive letters saying they have the disease. So in total, 9,999 + 99 = 10,098 would be told they have the disease when in fact only 99 of them do. And 99 is less than 1% of 10,098. So this would seem to be true. However, I brought this up on another forum, and some of the users have brought up some interesting counterpoints. Maybe you could read through the topic and let me know your thoughts. I've said basically everything I can think of to prove it! Here is the thread, read it! - http://www.blink-182online.com/forums/index.php?topic=58294.0 So let me know your thoughts, please!