But today try to ask a few people around you, and see what they say.
> Suppose you have a test that's 90% accurate in identifying people who have a disease, and 90% accurate in identifying people who do not have the disease. Assume that 4% of people have this disease. Hypothetical_Bob is tested, and the test says that he has the disease. What are the chances that Bob actually does have the disease?
Lots of people - smart people too! - struggle with this. Even if you give them pencil and paper and let them doodle around they will often give you an incorrect number. And most of them will be surprised if you tell them it's as low as 26%.
Ah yes, I see what you're saying. Real numbers are easier to reason with and get correct results than percentages.
I think my point is slightly orthogonal since I misunderstood you; if you tell someone that something is "10%" they will think "that is pretty bad" whereas "1 in 10" is more likely to get a "hey, that's not too shabby" response. Percentages sound "worse" than numbers, even when they are the same (at least to me). Perhaps because they are harder to reason with?
But today try to ask a few people around you, and see what they say.
> Suppose you have a test that's 90% accurate in identifying people who have a disease, and 90% accurate in identifying people who do not have the disease. Assume that 4% of people have this disease. Hypothetical_Bob is tested, and the test says that he has the disease. What are the chances that Bob actually does have the disease?
Lots of people - smart people too! - struggle with this. Even if you give them pencil and paper and let them doodle around they will often give you an incorrect number. And most of them will be surprised if you tell them it's as low as 26%.