Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (2018, CUP) Deborah G. Mayo Abstract for Book By disinterring the underlying statistical philosophies this book sets the stage for understanding and finally getting beyond today’s most pressing controversies revolving around statistical methods and irreproducible findings. Statistical Inference as Severe Testing takes the reader on […]

# Author: Mayo

## Deconstructing the Fisher-Neyman conflict wearing fiducial glasses + Excerpt 5.8 from SIST

This continues my previous post: “Can’t take the fiducial out of Fisher…” in recognition of Fisher’s birthday, February 17. These 2 posts reflect my working out of these ideas in writing Section 5.8 of Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (SIST, CUP 2018). Here’s all of Section 5.8 (“Neyman’s Performance […]

## Can’t Take the Fiducial Out of Fisher (if you want to understand the N-P performance philosophy) [i]

Continuing with posts in recognition of R.A. Fisher’s birthday, I post one from a few years ago on a topic that had previously not been discussed on this blog: Fisher’s fiducial probability. [Neyman and Pearson] “began an influential collaboration initially designed primarily, it would seem to clarify Fisher’s writing. This led to their theory of […]

## Guest Blog: R. A. Fisher: How an Outsider Revolutionized Statistics (Aris Spanos)

In recognition of R.A. Fisher’s birthday on February 17…a week of Fisher posts! ‘R. A. Fisher: How an Outsider Revolutionized Statistics’ by Aris Spanos Few statisticians will dispute that R. A. Fisher (February 17, 1890 – July 29, 1962) is the father of modern statistics; see Savage (1976), Rao (1992). Inspired by William Gosset’s (1908) […]

## R.A. Fisher: “Statistical methods and Scientific Induction”

I continue a week of Fisherian posts begun on his birthday (Feb 17). This is his contribution to the “Triad”–an exchange between Fisher, Neyman and Pearson 20 years after the Fisher-Neyman break-up. The other two are below. They are each very short and are worth your rereading. “Statistical Methods and Scientific Induction” by Sir Ronald […]

## Guest Post: STEPHEN SENN: ‘Fisher’s alternative to the alternative’

As part of the week of posts on R.A.Fisher (February 17, 1890 – July 29, 1962), I reblog a guest post by Stephen Senn from 2012, and 2017. See especially the comments from Feb 2017. ‘Fisher’s alternative to the alternative’ By: Stephen Senn [2012 marked] the 50th anniversary of RA Fisher’s death. It is a good […]

## Happy Birthday R.A. Fisher: ‘Two New Properties of Mathematical Likelihood’

Today is R.A. Fisher’s birthday. I will post some Fisherian items this week in honor of it*. This paper comes just before the conflicts with Neyman and Pearson erupted. Fisher links his tests and sufficiency, to the Neyman and Pearson lemma in terms of power. We may see them as ending up in a similar […]

## American Phil Assoc Blog: The Stat Crisis of Science: Where are the Philosophers?

The Statistical Crisis of Science: Where are the Philosophers? February 14, 2019 by Blog Contributor, by Deborah G. Mayo This was published today on the American Philosophical Association blog. “[C]onfusion about the foundations of the subject is responsible, in my opinion, for much of the misuse of the statistics that one meets in fields of application such as […]

## Summer Seminar in PhilStat: July 28-Aug 11

Please See New Information for Summer Seminar in PhilStat

## Little Bit of Logic (5 mini problems for the reader)

Little bit of logic (5 little problems for you)[i] Deductively valid arguments can readily have false conclusions! Yes, deductively valid arguments allow drawing their conclusions with 100% reliability but only if all their premises are true. For an argument to be deductively valid means simply that if the premises of the argument are all true, […]

## Mayo Slides Meeting #1 (Phil 6334/Econ 6614, Mayo & Spanos)

Slides Meeting #1 (Phil 6334/Econ 6614: Current Debates on Statistical Inference and Modeling (D. Mayo and A. Spanos)

## Excerpt from Excursion 4 Tour IV: More Auditing: Objectivity and Model Checking

4.8 All Models Are False . . . it does not seem helpful just to say that all models are wrong. The very word model implies simplification and idealization. . . . The construction of idealized representations that capture important stable aspects of such systems is, however, a vital part of general scientific analysis. (Cox 1995, p. 456) […]

## Protected: Participants in 6334/6614 Meeting place Jan-Feb

There is no excerpt because this is a protected post.

## Protected: 6334/6614 Bibliography With Links

There is no excerpt because this is a protected post.

## (Full) Excerpt of Excursion 4 Tour I: The Myth of “The Myth of Objectivity”

A month ago, I excerpted just the very start of Excursion 4 Tour I* on The Myth of the “Myth of Objectivity”. It’s a short Tour, and this continues the earlier post. 4.1 Dirty Hands: Statistical Inference Is Sullied with Discretionary Choices If all flesh is grass, kings and cardinals are surely grass, but so is […]

## New Course Starts Tomorrow: Current Debates on Statistical Inference and Modelings: Joint Phil and Econ

I will post items on a new PhilStat Spring 19 page on this blogI

## A letter in response to the ASA’s Statement on p-Values by Ionides, Giessing, Ritov and Page

I came across an interesting letter in response to the ASA’s Statement on p-values that I hadn’t seen before. It’s by Ionides, Giessing, Ritov and Page, and it’s very much worth reading. I make some comments below. Response to the ASA’s Statement on p-Values: Context, Process, and Purpose Edward L. Ionidesa, Alexander Giessinga, Yaacov Ritova, and […]

## Mementos from Excursion 4: Objectivity & Auditing: Blurbs of Tours I – IV

Excursion 4: Objectivity and Auditing (blurbs of Tours I – IV) Excursion 4 Tour I: The Myth of “The Myth of Objectivity” Blanket slogans such as “all methods are equally objective and subjective” trivialize into oblivion the problem of objectivity. Such cavalier attitudes are at odds with the moves to take back science […]

## Excerpt from Excursion 4 Tour II: 4.4 “Do P-Values Exaggerate the Evidence?”

Excerpt from Excursion 4 Tour II* 4.4 Do P-Values Exaggerate the Evidence? “Significance levels overstate the evidence against the null hypothesis,” is a line you may often hear. Your first question is: What do you mean by overstating the evidence against a hypothesis? Several (honest) answers are possible. Here is one possibility: What I […]

## January Invites: Ask me questions (about SIST), Write Discussion Analyses (U-Phils)

ASK ME. Some readers say they’re not sure where to ask a question of comprehension on Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (2018, CUP)–SIST– so here’s a special post to park your questions of comprehension (to be placed in the comments) on a little over the first half of […]