Archive for the ‘frequentism’ Category

Even with non-informative priors, the Bayesian approach is preferable to frequentist linear regression

December 2, 2013

A unique aspect of the Bayesian approach is that it allows one to integrate previous knowledge (“prior beliefs“) with current data (“likelihood“). Yet even in those cases in which non-informative priors are used (as in here and here) , the Bayesian approach is preferable due to its conservative nature.



Choosing a narrative in isolation: Fisher, Popper and p-values (Part II)

June 27, 2013

In the second part of this post we will see how one can reject an incomplete (from Popper’s perspective) scientific narrative using significance tests without making an appeal to the frequency interpretation of probability. Actually there are at least two paths, both of which can be seen as numerical approximations to a Bayesian selection procedure. (more…)

Choosing a narrative in isolation: Fisher, Popper and p-values (Part I)

June 26, 2013

Most applied work in scientific exploration also involves a choice among narratives: an experiment is designed on the basis of a premise being true and when the experiment is performed, data are collected and a paper is written. The latter (among other things) puts the data in the litmus of a statistical significance test to yield a p-value that the investigators use to reject the original hypothesis (if the p-value is small) or not reject it (if the p-value is large). Unfortunately large p-values usually have the undesired consequence that the research paper and the experiment are rejected from the scientific record, i.e. they are never accepted for publication: (more…)