Does statistics have an ontology? Does it need one? (draft 2) by D. Mayo.
From the post:
Chance, rational beliefs, decision, uncertainty, probability, error probabilities, truth, random sampling, resampling, opinion, expectations. These are some of the concepts we bandy about by giving various interpretations to mathematical statistics, to statistical theory, and to probabilistic models. But are they real? The question of “ontology” asks about such things, and given the “Ontology and Methodology” conference here at Virginia Tech (May 4, 5), I’d like to get your thoughts (for possible inclusion in a Mayo-Spanos presentation).* Also, please consider attending**.
Interestingly, I noticed the posts that have garnered the most comments have touched on philosophical questions of the nature of entities and processes behind statistical idealizations (e.g.,http://errorstatistics.com/2012/10/18/query/).
The post and ensuing comments offer much to consider.
From my perspective, if assumptions, ontological and otherwise, go unstated, the results opaque.
You can accept them, because they fit your prior opinion or how you wanted the results to be, or reject them as not fitting your prior opinion or desired result.