Lots of policy decisions are made based on statistics. Yet they are easy to fool someone with if he or she does not understand them properly enough.
In my experience, to a doctor, even a good one, _at first_ it's just an annoying thing they have to do to get published and they don't really understand the significance of significances.
Slightly disappointing. I'd have expected doctors to have an understanding of placebo effects, and the field of medicine is one where you regularly hear (even outside medicine) about studies being discredited afterwards for wrong/improper controls, positive results being unreproducible etc.
I don't remember the last time I heard a comp sci paper being withdrawn for bad statistics. (They tend to have none, even when they should)
I'm not saying doctors doing research never learn this stuff, just that they come out of University without this knowledge. (I certainly don't know enough about medical research literature to make a statement like this.)
Curiously, at one biomed lab (can't remember if it's the wife's) they have a dedicated person (shared by several labs) to do the statistics for the presentations and the papers. Kind of weird if you ask me, you'd think understanding whether your results are meaningful is not something you calculate at the end!
Lots of policy decisions are made based on statistics. Yet they are easy to fool someone with if he or she does not understand them properly enough.
In my experience, to a doctor, even a good one, _at first_ it's just an annoying thing they have to do to get published and they don't really understand the significance of significances.
Slightly disappointing. I'd have expected doctors to have an understanding of placebo effects, and the field of medicine is one where you regularly hear (even outside medicine) about studies being discredited afterwards for wrong/improper controls, positive results being unreproducible etc.
I don't remember the last time I heard a comp sci paper being withdrawn for bad statistics. (They tend to have none, even when they should)