h****r
发帖数: 258 | 1
folksinger 15 hours ago [-]
Let's take a recent election as an example:
A Bayesian pollster began with a certain set of prior probabilities. That
the college educated were more likely to vote in previous elections, for
example, informed the sample population, because it wouldn't make much sense
to ask the opinions of those who would stay home.
Thus, based on priors that were updated with new empirical data, a new set
of probabilities emerged, that gave a certain candidate a high probability
of victory.
Members of the voting public, aware of this high probability, decided that
this meant with certainty that this candidate would win and therefore
decided to stay home on election day.
In reality the Bayesian models were incorrect as amongst other factors, a
much higher number of non-college educated individuals decided to vote and
to vote for the other candidate. | N*******M
发帖数: 3963 | 2 a much higher number of non-college educated individuals, aka the
deplorables, aka the silent majority
【在 h****r 的大作中提到】
:
: folksinger 15 hours ago [-]
: Let's take a recent election as an example:
: A Bayesian pollster began with a certain set of prior probabilities. That
: the college educated were more likely to vote in previous elections, for
: example, informed the sample population, because it wouldn't make much sense
: to ask the opinions of those who would stay home.
: Thus, based on priors that were updated with new empirical data, a new set
: of probabilities emerged, that gave a certain candidate a high probability
: of victory.
| i**********a
发帖数: 1402 | 3
哈哈哈，very true
【在 N*******M 的大作中提到】
: a much higher number of non-college educated individuals, aka the
: deplorables, aka the silent majority
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