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.

## Archive for the ‘frequentism’ Category

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

December 2, 2013### Choosing a narrative in isolation: Fisher, Popper and p-values (Part II)

June 27, 2013In 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, 2013Most 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…)