Information and directions for joining our forum are here.
Upcoming talks will include Stephen Senn (Statistical consultant, Scotland, November 19, 2020); Deborah Mayo (Philosophy, Virginia Tech, December 19, 2020); and Alexander Bird (Philosophy, King’s College London, January 28, 2021). https://phil-stat-wars.com/schedule/.
In October, instead of our monthly meeting, I invite you to a P-value debate on October 15 sponsored by the National Institute of Statistical Science, with J. Berger, D. Mayo, and D. Trafimow. Register at https://www.niss.org/events/statistics-debate.
I will now hold a monthly remote forum on Phil Stat: The Statistics Wars and Their Casualties–the title of the workshop I had scheduled to hold at the London School of Economics (Centre for Philosophy of Natural and Social Science: CPNSS) on 19-20 June 2020. (See the announcement at the bottom of this blog). I held the graduate seminar in Philosophy (PH500) that was to precede the workshop remotely (from May 21-June 25), and this new forum will be both an extension of that and a linkage to the planned workshop. The issues are too pressing to put off for a future in-person workshop, which I still hope to hold. It will begin with presentations by workshop participants, with lots of discussion. If you want to be part of this monthly forum and engage with us, please go to the information and directions page. The links are now fixed, sorry. (It also includes readings for Aug 20.) If you are already on our list, you’ll automatically be notified of new meetings. (If you have questions, email me.) Continue reading
All: On July 30 (10am EST) I will give a virtual version of my JSM presentation, remotely like the one I will actually give on Aug 6 at the JSM. Co-panelist Stan Young may as well. One of our surprise guests tomorrow (not at the JSM) will be Yoav Benjamini! If you’re interested in attending our July 30 practice session* please follow the directions here. Background items for this session are in the “readings” and “memos” of session 5.
*unless you’re already on our LSE Phil500 list
JSM 2020 Panel Flyer (PDF)
JSM online program w/panel abstract & information): Continue reading
Ship StatInfasST will embark on a new journey from 21 May – 18 June, a graduate research seminar for the Philosophy, Logic & Scientific Method Department at the LSE, but given the pandemic has shut down cruise ships, it will remain at dock in the U.S. and use zoom. If you care to follow any of the 5 sessions, nearly all of the materials will be linked here collected from excerpts already on this blog. If you are interested in observing on zoom beginning 28 May, please follow the directions here.
For the updated schedule, see the seminar web page.
Topic: Current Controversies in Phil Stat
(LSE, Remote 10am-12 EST, 15:00 – 17:00 London time; Thursdays 21 May-18 June) Continue reading
(See my new blog
for specifics (phil-stat-wars.com).
I am co-running a workshop
from 19-20 June, 2020 at LSE (Center for the Philosophy of Natural and Social Sciences CPNSS), with Roman Frigg. Participants include:
(King’s College London), Mark Burgman
(Imperial College London), Daniele Fanelli
(LSE), David Hand
(Imperial College London), Christian Hennig
(University of Bologna), Katrin Hohl
(City University London), Daniël Lakens
(Eindhoven University of Technology), Deborah Mayo
(Virginia Tech), Richard Morey
(Cardiff University), Stephen Senn
If you have a particular Phil Stat event you’d like me to advertise, please send it to me.
In Tour II of this first Excursion of Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (SIST, 2018, CUP), I pull back the cover on disagreements between experts charged with restoring integrity to today’s statistical practice. Some advised me to wait until later (in the book) to get to this eye-opener. Granted, the full story involves some technical issues, but after many months, I think I arrived at a way to get to the heart of things informally (with a promise of more detailed retracing of steps later on). It was too important not to reveal right away that some of the most popular “reforms” fall down on the job even with respect to our most minimal principle of evidence (you don’t have evidence for a claim if little if anything has been done to probe the ways it can be flawed). Continue reading
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 evidential support–and in the first instance you should look not at full-blown Bayesian probabilism, but at comparative accounts that sidestep prior probabilities in hypotheses. An intuitively plausible logic of comparative support was given by the philosopher Ian Hacking (1965)–the Law of Likelihood. Fortunately, the Museum of Statistics is organized by theme, and the Law of Likelihood and the related Likelihood Principle is a big one. Continue reading
Please See New Information for Summer Seminar in PhilStat
Mayo and A. Spanos
PHIL 6334/ ECON 6614: Spring 2019: Current Debates on Statistical Inference and Modeling
Bibliography (this includes a selection of articles with links; numbers 1-15 after the item refer to seminar meeting number.)
See Syllabus (first) for class meetings, and the page PhilStat19 menu up top for other course items.
Achinstein (2010). Mill’s Sins or Mayo’s Errors? (E&I: 170-188). (11)
Bacchus, Kyburg, & Thalos (1990). Against Conditionalization, Synthese (85): 475-506. (15)
Barnett (1999). Comparative Statistical Inference (Chapter 6: Bayesian Inference), John Wiley & Sons. (1), (15)
Begley & Ellis (2012) Raise standards for preclinical cancer research. Nature 483: 531-533. (10)
I will post items on a new PhilStat Spring 19 page on this blogI
First draft of PhilStat Announcement
Excerpts from the Preface:
The Statistics Wars:
Today’s “statistics wars” are fascinating: They are at once ancient and up to the minute. They reflect disagreements on one of the deepest, oldest, philosophical questions: How do humans learn about the world despite threats of error due to incomplete and variable data? At the same time, they are the engine behind current controversies surrounding high-profile failures of replication in the social and biological sciences. How should the integrity of science be restored? Experts do not agree. This book pulls back the curtain on why. Continue reading
I predicted that the degree of agreement behind the ASA’s “6 principles” on p-values , partial as it was,was unlikely to be replicated when it came to most of the “other approaches” with which some would supplement or replace significance tests– notably Bayesian updating, Bayes factors, or likelihood ratios (confidence intervals are dual to hypotheses tests). [My commentary is here.] So now they may be advising a “hold off” or “go slow” approach until some consilience is achieved. Is that it? There’s word that the ASA will hold meeting where the other approaches are put through their paces. I don’t know when. I was tweeted an article about the background chatter taking place behind the scenes; I wasn’t one of people interviewed for this. Here are some excerpts, I may add more later after it has had time to sink in.
“Restoring Credibility in Statistical Science: Proceed with Caution Until a Balanced Critique Is In”
J. Hossiason Continue reading
SNEAK PREVIEW: Here’s the cover of Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars:
It should be out in July 2018. The “Itinerary”, generally known as the Table of Contents, is below. I forgot to mention that this is not the actual pagination, I don’t have the page proofs yet. These are the pages of the draft I submitted. It should be around 50 pages shorter in the actual page proofs, maybe 380 pages.
I was part of something called “a brains blog roundtable” on the business of p-values earlier this week–I’m glad to see philosophers getting involved.
Next week I’ll be in a session that I think is intended to explain what’s right about P-values at an ASA Symposium on Statistical Inference : “A World Beyond p < .05”. Continue reading