by Summary:
Similar to there Bayesian versus frequentist debate in statistical reasoning.Likelihood Principle My epistemological view on this is that the border between them is fuzzy and needs to be approached on a case by case basis, along with acknowledging a cognitive bias toward greater certainty than is attainable from the given and the reasoning about it. Humans don't like uncertainty and have a strong bias toward minimizing it at the risk of fooling themselves. Even statisticians. Error Statistics G.A. Barnard: The “catch-all” factor: probability vs likelihood Debate between G. A. Barnard and Leonard Jimmie Savage Posted by Deborah Mayo, professor in the Department of Philosophy at Virginia Tech and visiting professor at the Center for the Philosophy of Natural and Social Science
Topics:
Mike Norman considers the following as important: likelihood, probability, statistical inference, statistical reasoning
This could be interesting, too:
Similar to there Bayesian versus frequentist debate in statistical reasoning.Likelihood Principle My epistemological view on this is that the border between them is fuzzy and needs to be approached on a case by case basis, along with acknowledging a cognitive bias toward greater certainty than is attainable from the given and the reasoning about it. Humans don't like uncertainty and have a strong bias toward minimizing it at the risk of fooling themselves. Even statisticians. Error Statistics G.A. Barnard: The “catch-all” factor: probability vs likelihood Debate between G. A. Barnard and Leonard Jimmie Savage Posted by Deborah Mayo, professor in the Department of Philosophy at Virginia Tech and visiting professor at the Center for the Philosophy of Natural and Social Science
Topics:
Mike Norman considers the following as important: likelihood, probability, statistical inference, statistical reasoning
This could be interesting, too:
Mike Norman writes Lars P. Syll — On the applicability of statistics in social sciences
Mike Norman writes Andrew Gelman — Our hypotheses are not just falsifiable; they’re actually false.
Mike Norman writes Lars P. Syll — Truth and probability
Mike Norman writes Andrew Gelman — Gaydar and the fallacy of objective measurement
Similar to there Bayesian versus frequentist debate in statistical reasoning.
My epistemological view on this is that the border between them is fuzzy and needs to be approached on a case by case basis, along with acknowledging a cognitive bias toward greater certainty than is attainable from the given and the reasoning about it.
Humans don't like uncertainty and have a strong bias toward minimizing it at the risk of fooling themselves. Even statisticians.
Error Statistics
G.A. Barnard: The “catch-all” factor: probability vs likelihood
Debate between G. A. Barnard and Leonard Jimmie Savage
Posted by Deborah Mayo, professor in the Department of Philosophy at Virginia Tech and visiting professor at the Center for the Philosophy of Natural and Social Science of the London School of Economics.
Posted by Deborah Mayo, professor in the Department of Philosophy at Virginia Tech and visiting professor at the Center for the Philosophy of Natural and Social Science of the London School of Economics.