by Summary:
Here: Philip Pilkington, “Why the Pollsters totally failed to call a Trump Victory, Why I (sort of) succeeded – and Why you should listen to neither of us,” Fixing the Economists, 14 November, 2016.A good discussion.Probabilities can be categorised into the following types:(1) a priori probabilities (which are analytic a priori and necessarily true), and(2) a posteriori probabilities (which are contingent and empirical), further divided into:(a) relative frequency probabilities; (b) epistemic probabilities.To cut a long story short, even if the media have well sampled polls (not biased or oversampled), the numerical probability estimates they create from these polls for the probability of an outcome on election day are not objective probability scores in the way that a priori probabilities are objective. The numerical probability estimates that the media and pollsters give us are subjective, even if when they are based on good poll data.And they certainly aren’t proper relative frequency probabilities of Type 1.a either. Our estimate of how probable an outcome on election day is likely to be is essentially an epistemic probability.A more technical discussion of probability here.
Topics:
Lord Keynes considers the following as important: An Analysis of Why the Polls were Wrong on Trump
This could be interesting, too:
Here:Here: Philip Pilkington, “Why the Pollsters totally failed to call a Trump Victory, Why I (sort of) succeeded – and Why you should listen to neither of us,” Fixing the Economists, 14 November, 2016.A good discussion.Probabilities can be categorised into the following types:(1) a priori probabilities (which are analytic a priori and necessarily true), and(2) a posteriori probabilities (which are contingent and empirical), further divided into:(a) relative frequency probabilities; (b) epistemic probabilities.To cut a long story short, even if the media have well sampled polls (not biased or oversampled), the numerical probability estimates they create from these polls for the probability of an outcome on election day are not objective probability scores in the way that a priori probabilities are objective. The numerical probability estimates that the media and pollsters give us are subjective, even if when they are based on good poll data.And they certainly aren’t proper relative frequency probabilities of Type 1.a either. Our estimate of how probable an outcome on election day is likely to be is essentially an epistemic probability.A more technical discussion of probability here.
Topics:
Lord Keynes considers the following as important: An Analysis of Why the Polls were Wrong on Trump
This could be interesting, too:
Philip Pilkington, “Why the Pollsters totally failed to call a Trump Victory, Why I (sort of) succeeded – and Why you should listen to neither of us,” Fixing the Economists, 14 November, 2016.A good discussion.
Probabilities can be categorised into the following types:
(1) a priori probabilities (which are analytic a priori and necessarily true), andTo cut a long story short, even if the media have well sampled polls (not biased or oversampled), the numerical probability estimates they create from these polls for the probability of an outcome on election day are not objective probability scores in the way that a priori probabilities are objective. The numerical probability estimates that the media and pollsters give us are subjective, even if when they are based on good poll data.(2) a posteriori probabilities (which are contingent and empirical), further divided into:
(a) relative frequency probabilities;(b) epistemic probabilities.
And they certainly aren’t proper relative frequency probabilities of Type 1.a either.
Our estimate of how probable an outcome on election day is likely to be is essentially an epistemic probability.
A more technical discussion of probability here.