Posts Tagged With: RMM

RMM-8: New Mayo paper: “StatSci and PhilSci: part 2 (Shallow vs Deep Explorations)”

A new article of mine,  “Statistical Science and Philosophy of Science Part 2: Shallow versus Deep Explorations” has been published in the on-line journal, Rationality, Markets, and Morals (Special Topic: Statistical Science and Philosophy of Science: Where Do/Should They Meet?”).

The contributions to this special volume began with the conference we ran in June 2010. (See web poster.)   My first article in this collection was essentially just my introduction to the volume, whereas this new one discusses my work. If you are a reader of this blog, you will recognize portions from early posts, as I’d been revising it then.

The sections are listed below. I will be posting portions in the next few days. We invite comments for this blog, and for possible publication in this special volume of RMM, if received before the end of this year.

This is the 8th RMM announcement. Many thanks to Sailor for digging up the previous 7, and listing them at the end*. (The paper’s title stemmed from the Deepwater Horizon oil spill of spring 2010**).


Inability to clearly defend against the criticisms of frequentist methods has turned many a frequentist away from venturing into foundational battlegrounds. Conceding the distorted perspectives drawn from overly literal and radical expositions of what Fisher, Neyman, and Pearson ‘really thought’, some deny they matter to current practice. The goal of this paper is not merely to call attention to the howlers that pass as legitimate criticisms of frequentist error statistics, but also to sketch the main lines of an alternative statistical philosophy within which to better articulate the roles and value of frequentist tools.

Statistical Science Meets Philosophy of Science Part 2:
Shallow versus Deep Explorations

 1. Comedy Hour at the Bayesian Retreat

2. Popperians Are to Frequentists as Carnapians Are to Bayesians
2.1 Severe Tests
2.2 Another Egregious Violation of the Severity Requirement
2.3 The Rationale for Severity is to Find Things Out Reliably
2.4 What Can Be Learned from Popper; What Can Popperians Be Taught?

3. Frequentist Error-Statistical Tests
3.1 Probability in Statistical Models of Experiments
3.2 Statistical Test Ingredients
3.3. Hypotheses and Events
3.4. Hypotheses Inferred Need Not Be Predesignated Continue reading

Categories: Philosophy of Statistics, Statistics | Tags: ,

Earlier U-Phils and Deconstructions

Dear Reader: If you wish to see some previous rounds of philosophical analyses and deconstructions on this blog, we’ve listed some of them below:(search this blog under “U-Phil” for more)

Introductory explanation:

Mayo on Jim Berger:

Contributed deconstructions of J. Berger:

J. Berger on J. Berger:

Mayo on Senn:

Others on Senn:

Gelman on Senn:

Senn on Senn:

Mayo, Senn & Wasserman on Gelman:

Hennig on Gelman:

Deconstructing Dutch books:

Deconstructing Larry Wasserman

Aris Spanos on Larry Wasserman

Hennig and Gelman on Wasserman

Wasserman replies to Spanos and Hennig

concluding the deconstruction: Wasserman-Mayo


There are  others, but this should do; if you care to write on my previous post (send directly to


D Mayo

Categories: philosophy of science, U-Phil | Tags: , ,

RMM-6: Special Volume on Stat Sci Meets Phil Sci

The article “The Renegade Subjectivist: José Bernardo’s Reference Bayesianism” by Jan Sprenger has now been published in our special volume of the on-line journal, Rationality, Markets, and Morals (Special Topic: Statistical Science and Philosophy of Science: Where Do/Should They Meet?)

Abstract: This article motivates and discusses José Bernardo’s attempt to reconcile the  subjective Bayesian framework with a need for objective scientific inference, leading to a special kind of objective Bayesianism, namely reference Bayesianism. We elucidate principal ideas and foundational implications of Bernardo’s approach, with particular attention to the classical problem of testing a precise null hypothesis against an unspecified alternative.

Categories: Philosophy of Statistics, Statistics | Tags: , ,

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