Belief-Sustaining Inference

TL;DR: If you’re in Pittsburgh today, come to SIGBOVIK 2014 at CMU at 5pm for free food and incredible math!

In a recent chat with my classmate Alex Reinhart, author of Statistics Done Wrong, we noticed a major gap in statistical inference philosophies. Roughly speaking, Bayesian statisticians begin with a prior and a likelihood, while Frequentist statisticians use the likelihood alone. Obviously, there is scope for a philosophy based on the prior alone.

We began to develop this idea, calling it Belief-Sustaining Inference, or BS for short. We discovered that BS inference is extremely efficient, for instance getting by with smaller sample sizes and producing tighter confidence intervals than other inference philosophies.

Today I am proud dismayed complacent to report that our resulting publication has been accepted to the prestigious adequate SIGBOVIK 2014 conference (for topics such as Inept Expert Systems, Artificial Stupidity, and Perplexity Theory):

Reinhart, A. and Wieczorek, J. “Belief-Sustaining Inference.” SIGBOVIK Proceedings, Pittsburgh, PA: Association for Computational Heresy, pp. 77-81, 2014. (pdf)

Our abstract:

Two major paradigms dominate modern statistics: frequentist inference, which uses a likelihood function to objectively draw inferences about the data; and Bayesian methods, which combine the likelihood function with a prior distribution representing the user’s personal beliefs. Besides myriad philosophical disputes, neither method accurately describes how ordinary humans make inferences about data. Personal beliefs clearly color decision-making, contrary to the prescription of frequentism, but many closely-held beliefs do not meet the strict coherence requirements of Bayesian inference. To remedy this problem, we propose belief-sustaining (BS) inference, which makes no use of the data whatsoever, in order to satisfy what we call “the principle of least embarrassment.” This is a much more accurate description of human behavior. We believe this method should replace Bayesian and frequentist inference for economic and public health reasons.

If you’re around CMU today (April 1st), please do stop by SIGBOVIK at 5pm, in Rashid Auditorium in the Gates-Hillman Center. There will be free food, and that’s no joke.