Seriously, if you define evidence as "something that sways your beliefs because it is more likely to happen under one hypothesis than the alternative hypothesis," then Bayesianism is the math of evidence, and frequentism (which is used in "Real science") is not. (and does not even really try to be)
This looks seriously misleading to me. While it may be technically correct (because neither frequentism nor "Real science" care much about swaying your beliefs), the math of deciding what's "more likely to happen under one hypothesis than the alternative hypothesis" is a standard part of frequentist statistics where it goes by the name of maximum likelihood.
You might also be interested in the concept of Fisher information.
I agree with you criticism. Thank you.
After the terrorist attacks at Charlie Hebdo, conspiracy theories quickly arose about who was behind the attacks.
People who are critical to the west easily swallow such theories while pro-vest people just as easily find them ridiculous.
I guess we can agree that the most rational response would be to enter a state of aporia until sufficient evidence is at hand.
Yet very few people do so. People are guided by their previous understanding of the world, when judging new information. It sounds like a fine Bayesian approach for getting through life, but for real scientific knowledge, we can't rely on *prior* reasonings (even though these might involve Bayesian reasoning). Real science works by investigating evidence.
So, how do we characterise the human tendency to jump to conclusions that have simply been supplied by their sense of normativity. Is their a previously described bias that covers this case?