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The fix is to use Bayesian statistics, where every finding updates you beliefs and therefore there is no such thing as a null result. The cult of the p value n
by 08-15 8y ago
The fix is to use Bayesian statistics, where every finding updates you beliefs and therefore there is no such thing as a null result. The cult of the p value needs to end.
- jononor 8y agoAre there any practical introductions/guides to applying this method? Interested for my own research.
- 08-15 8y agoE.T.Jaynes: "Probability Theory, The Logic Of Science" A great introduction to the topic and a great general guideline. It's not a collection of recipes, more like a nudge in a direction where you don't need canned recipes anymore.
- pbhjpbhj 8y agoSurely that only works if your hypothesis is partly right?
- 08-15 8y agoI don't know how a hypothesis can be partly right, but I'll read this as "Surely that only works if your prior belief in your hypothesis is neither exactly 0 nor 1?" And that's correct. Prior distributions are never completely concentrated at either extreme, for those could never be updated. If your hypothesis is now totally wrong, your confidence in it (the posterior probability) will converge toward zero.
- jonnycomputer 8y agoIf a hypothesis is considered as a species of proposition, then yes, there are a variety of ways in which a hypothesis can be "partly true". Firstly, if the hypothesis is a conjunction, the some of the conjuncts could be true. Propositions can also contain vague predicates with ambiguous truth values. Finally, there is the truthlikeness of the propositions. Some propositions seem to be more true, or have more versimiltude, than others (for which I refer you to https://plato.stanford.edu/entries/truthlikeness/ https://plato.stanford.edu/entries/truthlikeness/)
- 08-15 8y agoIf that is indeed what GP meant, then no, truthlikeness is completely irrelevant to Bayesian reasoning.