Let’s play doctor.
Let’s say you have a patient who shows signs of a disease that’s tricky to diagnose. In fact, of the people who show these symptoms, only 1 in 100 have the disease. The test is only successful in detecting the disease 90% of the time. The test can also fail by incorrectly indicating a “false positive” (i.e., test results show you have the disease when in fact, you do not) 9% of the time.
How do you feel about them odds?
- Track the “patient does not have the disease” part of the equation. Using numbers from above, 99 do not have the disease, 9% false positive is about 9 people.
- Compare that to the “correct positive” of the 1 person who has the disease and gets a positive result”. Let’s round up and say it’s one person.
Nine false positives to one correct positive. Feeling lucky?