Basic probability is useful to understand, and basic numeracy is useful. Not necessarily on an intuitive level, but on a level where you can back-of-the-envelope or do rough approximations if they are useful (chance of rain, chance of false positive vs disease, etc.)
B is not very useful to really get into unless you are in ML/stats or related area.
I think for most people the limiting factors in “being less crazy” have to do with interpersonal stuff, not math.
Frankly getting the data seems to be harder to get than the hardness of the calculation. If there is any website that tells you how often did it rain on the 9th April in your region in the last 25 years and how often did it rain between 1 and 15 April in the last 5 years (these are the most relevant data, right?), they may as well do the math themselves. Better yet, meterologists, who hopefully know some Bayes, can combine it with the specific information like current high and low pressure zones and cloud radars, and make predictions. Probably the best idea is to use theirs.
BTW can anyone confirm that meterologists know some Bayes? If August is normally dry as fsck in your region they should be fairly skeptical about specific evidences that suggest rain. While if October is normally torrential then even the slightest evidence of rain should count as one...
Basic probability is useful to understand, and basic numeracy is useful. Not necessarily on an intuitive level, but on a level where you can back-of-the-envelope or do rough approximations if they are useful (chance of rain, chance of false positive vs disease, etc.)
B is not very useful to really get into unless you are in ML/stats or related area.
I think for most people the limiting factors in “being less crazy” have to do with interpersonal stuff, not math.
Frankly getting the data seems to be harder to get than the hardness of the calculation. If there is any website that tells you how often did it rain on the 9th April in your region in the last 25 years and how often did it rain between 1 and 15 April in the last 5 years (these are the most relevant data, right?), they may as well do the math themselves. Better yet, meterologists, who hopefully know some Bayes, can combine it with the specific information like current high and low pressure zones and cloud radars, and make predictions. Probably the best idea is to use theirs.
BTW can anyone confirm that meterologists know some Bayes? If August is normally dry as fsck in your region they should be fairly skeptical about specific evidences that suggest rain. While if October is normally torrential then even the slightest evidence of rain should count as one...