Monthly Archives: October 2013

(I’m frustrated with the length this post and how much time it’s taking me to finish, so I’m splitting it into two parts.)

I subscribe to a school of thought some call “Jaynesian” after Edwin T. Jaynes. Its foundation is a theorem of Richard T. Cox, a physicist who studied electric eels, not to be confused with the eminent statistician Sir David R. Cox. Since my first project will be to engage with Professor Mayo’s  diametrically opposed views on the proper way to use (and think about the use of) statistics in science, it seems worthwhile to describe the theorem and the reasons I take it to be foundational to statistics — of the Bayesian variety, at least.

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In the Dark

A blog about the Universe, and all that surrounds it

Minds aren't magic

Paul Crowley

Mad (Data) Scientist

Musings, useful code etc. on R and data science


Reasoning about reasoning, mathematically.

The Accidental Statistician

Occasional ramblings on statistics

Slate Star Codex

"Talks a good game about freedom when out of power, but once he’s in - bam! Everyone's enslaved in the human-flourishing mines."

Models Of Reality

Stochastic musings of a biostatistician.

Data Colada

Thinking about evidence and vice versa

Hacked By Gl0w!Ng - F!R3

Stochastic musings of a biostatistician.

John D. Cook

Stochastic musings of a biostatistician.

Simply Statistics

Stochastic musings of a biostatistician.

Less Wrong

Stochastic musings of a biostatistician.

Normal Deviate

Thoughts on Statistics and Machine Learning

Xi'an's Og

an attempt at bloggin, nothing more...