Monthly Archives: May 2021

Bayesian philosophers vs Bayesian statisticians: Remarks on Jon Williamson

While I would agree that there are differences between Bayesian statisticians and Bayesian philosophers, those differences don’t line up with the ones drawn by Jon Williamson in his presentation to our Phil Stat Wars Forum (May 20 slides). I hope Bayesians (statisticians, or more generally, practitioners, and philosophers) will weigh in on this. 

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Categories: Phil Stat Forum, stat wars and their casualties | 11 Comments

Mayo Casualties of O-Bayesianism and Williamson response

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After Jon Williamson’s talk, Objective Bayesianism from a Philosophical Perspective, at the PhilStat forum on May 22, I raised some general “casualties” encountered by objective, non-subjective or default Bayesian accounts, not necessarily Williamson’s. I am pasting those remarks below, followed by some additional remarks and the video of his responses to my main kvetches. Continue reading

Categories: frequentist/Bayesian, objective Bayesians, Phil Stat Forum | 4 Comments

May 20: “Objective Bayesianism from a Philosophical Perspective” (Jon Williamson)

The ninth meeting of our Phil Stat Forum*:

The Statistics Wars
and Their Casualties

20 May 2021

TIME: 15:00-16:45 (London); 10:00-11:45 (New York, EST)

For information about the Phil Stat Wars forum and how to join, click on this link.

“Objective Bayesianism from a philosophical perspective” 

Jon Williamson Continue reading

Categories: Error Statistics | Tags:

Tom Sterkenburg Reviews Mayo’s “Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars” (2018, CUP)

T. Sterkenburg

Tom Sterkenburg, PhD
Postdoctoral Fellow
Munich Center for Mathematical Philosophy
LMU Munich
Munich, German

Deborah G. Mayo: Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars

The foundations of statistics is not a land of peace and quiet. “Tribal warfare” is perhaps putting it too strong, but it is the case that for decades now various camps and subcamps have been exchanging heated arguments about the right statistical methodology. That these skirmishes are not just an academic exercise is clear from the widespread use of statistical methods, and contemporary challenges that cry for more secure foundations: the rise of big data, the replication crisis.

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Categories: SIST, Statistical Inference as Severe Testing–Review, Tom Sterkenburg

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