Introduction & Overview The Meaning of My Title: Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars* 05/19/18 Blurbs of 16 Tours: Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (SIST) 03/05/19 Excursion 1 EXCERPTS Tour I Excursion 1 Tour I: Beyond Probabilism and Performance: Severity Requirement (1.1) […]

# Author: Mayo

## Excerpts: Final Souvenir Z, Farewell Keepsake & List of Souvenirs

We’ve reached our last Tour (of SIST)*: Pragmatic and Error Statistical Bayesians (Excursion 6), marking the end of our reading with Souvenir Z, the final Souvenir, as well as the Farewell Keepsake in 6.7. Our cruise ship Statinfasst, currently here at Thebes, will be back at dock for maintenance for our next launch at the […]

## (full) Excerpt: Excursion 5 Tour I — Power: Pre-data and Post-data (from “SIST: How to Get Beyond the Stat Wars”)

It’s a balmy day today on Ship StatInfasST: An invigorating wind has a salutary effect on our journey. So, for the first time I’m excerpting all of Excursion 5 Tour I (proofs) of Statistical Inference as Severe Testing How to Get Beyond the Statistics Wars (2018, CUP) A salutary effect of power analysis is that […]

## If you like Neyman’s confidence intervals then you like N-P tests

Neyman, confronted with unfortunate news would always say “too bad!” At the end of Jerzy Neyman’s birthday week, I cannot help imagining him saying “too bad!” as regards some twists and turns in the statistics wars. First, too bad Neyman-Pearson (N-P) tests aren’t in the ASA Statement (2016) on P-values: “To keep the statement reasonably […]

## If you like Neyman’s confidence intervals then you like N-P tests

Neyman, confronted with unfortunate news would always say “too bad!” At the end of Jerzy Neyman’s birthday week, I cannot help imagining him saying “too bad!” as regards some twists and turns in the statistics wars. First, too bad Neyman-Pearson (N-P) tests aren’t in the ASA Statement (2016) on P-values: “To keep the statement reasonably […]

## Neyman: Distinguishing tests of statistical hypotheses and tests of significance might have been a lapse of someone’s pen

I’ll continue to post Neyman-related items this week in honor of his birthday. This isn’t the only paper in which Neyman makes it clear he denies a distinction between a test of statistical hypotheses and significance tests. He and E. Pearson also discredit the myth that the former is only allowed to report pre-data, fixed error probabilities, and are […]

## Neyman vs the ‘Inferential’ Probabilists

We celebrated Jerzy Neyman’s Birthday (April 16, 1894) last night in our seminar: here’s a pic of the cake. My entry today is a brief excerpt and a link to a paper of his that we haven’t discussed much on this blog: Neyman, J. (1962), ‘Two Breakthroughs in the Theory of Statistical Decision Making‘ [i] […]

## Jerzy Neyman and “Les Miserables Citations” (statistical theater in honor of his birthday yesterday)

My second Jerzy Neyman item, in honor of his birthday, is a little play that I wrote for Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (2018): A local acting group is putting on a short theater production based on a screenplay I wrote: “Les Miserables Citations” (“Those Miserable Quotes”) [1]. The […]

## A. Spanos: Jerzy Neyman and his Enduring Legacy

Today is Jerzy Neyman’s birthday. I’ll post various Neyman items this week in recognition of it, starting with a guest post by Aris Spanos. Happy Birthday Neyman! A Statistical Model as a Chance Mechanism Aris Spanos Jerzy Neyman (April 16, 1894 – August 5, 1981), was a Polish/American statistician[i] who spent most of his professional career […]

## Several reviews of Deborah Mayo’s new book, Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars « Statistical Modeling, Causal Inference, and Social Science

Source: Several reviews of Deborah Mayo’s new book, Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars « Statistical Modeling, Causal Inference, and Social Science

## Excursion 1 Tour II: Error Probing Tools versus Logics of Evidence-Excerpt

For the first time, I’m excerpting all of Excursion 1 Tour II from SIST (2018, CUP). 1.4 The Law of Likelihood and Error Statistics If you want to understand what’s true about statistical inference, you should begin with what has long been a holy grail–to use probability to arrive at a type of logic of […]

## there’s a man at the wheel in your brain & he’s telling you what you’re allowed to say

It seems like every week something of excitement in statistics comes down the pike. Last week I was contacted by Richard Harris (and 2 others) about the recommendation to stop saying the data reach “significance level p” but rather simply say “the p-value is p”. (For links, see my previous post.) Friday, he wrote to […]

## Diary For Statistical War Correspondents on the Latest Ban on Speech

When science writers, especially “statistical war correspondents”, contact you to weigh in on some article, they may talk to you until they get something spicy, and then they may or may not include the background context. So a few writers contacted me this past week regarding this article (“Retire Statistical Significance”)–a teaser, I now suppose, […]

## 3 Days to Apply for the Summer Seminar in Phil Stat

Go to the website for instructions: SummerSeminarPhilStat.com.

## Protected: S. Senn: To infinity and beyond: how big are your data, really? (guest post)

There is no excerpt because this is a protected post.

## Blurbs of 16 Tours: Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (SIST)

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 […]

## 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 […]