Suppose an airport must decide whether to spend money to purchase some new equipment, while critics argue that the money should be spent on other aspects of airport safety. Slovic et. al. (2002) presented two groups of subjects with the arguments for and against purchasing the equipment, with a response scale ranging from 0 (would not support at all) to 20 (very strong support). One group saw the measure described as saving 150 lives. The other group saw the measure described as saving 98% of 150 lives. The hypothesis motivating the experiment was that saving 150 lives sounds vaguely good—is that a lot? a little?—while saving 98% of something is clearly very good because 98% is so close to the upper bound of the percentage scale. Lo and behold, saving 150 lives had mean support of 10.4, while saving 98% of 150 lives had mean support of 13.6.

I find this very interesting, but I think if people would both work hard enough to multiply 98% by 150 and would be educated about biases of the human brain than people would support the right things more often.

This is another problem with school. School(at lower levels especially) teaches things that is unimportant but doesn't teach useful stuff. For example, states and capitals of the U.S. can be googled in less than thirty seconds but bayes thereom and overcoming biases can't.