2023 Syllabus for Philosophy of Inductive-Statistical Inference

PHIL 6014 (crn: 20919): Spring 2023 

Philosophy of Inductive-Statistical Inference
(This is an IN-PERSON class*)
Wed 4:00-6:30 pm, McBryde 223
(Office hours: Tuesdays 3-4; Wednesdays 1:30-2:30)

Syllabus: Second Installment (PDF)

D. Mayo (2018) Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (SIST) CUP, 2018: SIST (electronic and paper provided to those taking the class; proofs are at errorstatistics.com, see below).
Supplemental text: Hacking, I. (2001). An introduction to probability and inductive logic. Cambridge University Press.
Articles from the Captain’s Bibliography (links to new articles will be provided). Other useful information can be found on the SIST Abstracts & Keywords and this post with SIST Excerpts & Mementos)

Date Themes/readings
1. 1/18       Introduction to the Course:
How to tell what’s true about statistical inference

(1/18/23 SLIDES here)

Reading: Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (SIST): Preface, Excursion 1 Tour I 1.1-1.3, 9-29

MISC: Souvenir A; SIST Abstracts & Keywords for all excursions and tours
2. 1/25
Q #2
Error Probing Tools vs Comparative Evidence: Likelihood & Probability
What counts as cheating?
Intro to Logic: arguments validity & soundness

(1/25/23 SLIDES here)

Reading: SIST: Excursion 1 Tour II 1.4-1.5, 30-55
Session #2 Questions: (PDF)

MISC: NOTES on Excursion 1, SIST: Souvenirs B, C & D, Logic Primer (PDF)
3. 2/1
   Q #3
Induction and Confirmation: PhilStat & Formal Epistemology
The Traditional Problem of Induction
Is Probability a Good Measure of Confirmation? Tacking Paradox

(2/1/23 SLIDES here)

Reading: SIST: Excursion 2, Tour I: 2.1-2.2, 59-74
Hacking “The Basic Rules of Probability” Hand Out (PDF)
UPDATED: Session #3 Questions: (PDF)

MISC: Excursion 2 Tour I Blurb & notes
4. 2/8 &
5. 2/15
Assign 1 2/15 
Falsification, Science vs Pseudoscience, Induction
Statistical Crises of Replication in Psychology & other sciences
Popper, severity and novelty, array of problems and models
Fallacies of rejection, Duhem’s problem; solving induction now

(/2/8/23 SLIDES here)

Reading for 2/8: Popper, Ch 1 from Conjectures and Refutations up to p. 59. (PDF),
This class overlaps with the next, so if you have time read Excursion 2, Tour II: (p. 75-82); Exhibit vi. (p. 82); and p. 108

Session #4 Questions: (PDF)
MISC (2/8): Self-quiz on Popper for Fun! (PDF); Cartoon Guide to Statistics (Link to VT Library link is here)
Reading for 2/15: SIST: Excursion 2, Tour II: read sections that interest you from those not covered last week. You can choose the example in 2.6 (or one from your field) or the discussion of solving induction in 2.7. Optional for 2/15: Gelman & Loken (2014)

(2/15/23 SLIDES here)

ASSIGNMENT 1 (due 2/15) (PDF)
MISC (2/15): SIST Souvenirs (E), (F), (G), (H); Excursion 2 Tour II Blurb & notes
  Fisher Birthday: February 17: Celebration on 2/22
6. 2/22
 Q #6
7. 3/1


Ingenious and Severe Tests: Fisher, Neyman-Pearson, Cox: Concepts of Tests

Reading for 2/22 from SIST: Excursion 3 Tour I: 3.1-3.3: read the sections that interest you, choosing to focus on the statistical tests, the history and philosophy of Fisher, Neiman and Pearson, the example of GTR. Choose 2 from the Triad (they’re very short): Fisher (1955), Pearson (1955), Neyman (1956)

(2/22/23 SLIDES here)

Session #6 Questions: (PDF)

Optional: The pathological Fisher (fiducial) and Neyman (performance) battle: SIST 388-391


Reading for 3/1: Sections from SIST skipped last week: Excursion 3 Tour I: (If time, look at the discussion of trade-offs 328-330) If interested in fiducial frequencies, see Neyman’s Performance and Fisher’s fiducial Section 5.8
Optional: Excursion 3 tour II: It’s the methods, stupid!

(3/1/23 SLIDES here)

MISC: Excursion 3 Tour I Blurb & notes; Souvenirs (I), (J), (K)
Morey app including Examples & Instructions (here);(Morey app) (SEV Apps)

SPRING BREAK Statistical Exercises While Sunning (March 4-12)

Sessions #11-14 are tentative;  please have a look at what’s in them so we can decide which to skip 
8. 3/15
Assign 2
Deeper Concepts (2 parts): Stat in the Higg’s discovery, and Confidence intervals and their duality with tests

Reading (for first part): Excursion 3 Tour III, 3.8 Higgs Discovery (See the ASA 6 principles on P-values: Note 4, P. 216, and Live Exhibit (ix) p. 200: Souv. N p. 201
Reading (for second part): Excursion 3 Tour III, 3.7: pp. 189-195

Assignment 2
(PDF) due 3/17/23

(3/15/23 (revised) SLIDES here)

Misc. Excursion 3 Tour III blurb & notes
9. 3/22

Testing Assumptions of Statistical Models (Guest Speaker: Aris Spanos on misspecification testing in statistics)

Reading: Excursion 4 Tour IV 4.8

(3/22/23 A. Spanos’ SLIDES here)

Misc. Excursion 4 Tour IV blurb & notes

10. 3/29


Who’s Exaggerating what? Bayes factors and Bayes/Fisher Disagreement, Jeffreys-Lindley Paradox (Guest Speaker: Richard Morey on Bayes Factors)

Reading. Excursion 4 Tour II 
(We are spend 2 weeks on this.)

Misc. Excursion 4 Tour II blurb & notes

11. 4/5

Mini essay

More on: Bayes factors and Bayes/Fisher Disagreement, Jeffreys-Lindley Paradox

Optional for those interested in objectivity in statistics:
Excursion 4 Tour I: 4.1, 4.2; 221-238
Peek Ahead: 6.7 Farewell Keepsake: 436-444 
Mini-essay (PDF)
12. 4/12

Biasing Selection Effects and Randomization

Reading: Excursion 4 Tour III  

(optional 5.7 Statistical Theatre: “Les Miserables Citations”: 371-381)
13. 4/19

Assign 3

Power: Pre-data and Post-data

Reading: Excursion 5 Tour I
14. 4/26 Positive Predictive Value and Probabilistic Instantiation

Controversies about inferring probabilities from frequencies (in law and epistemology)

Reading: Selection from Section 5.6 (excursion 5 Tour II); C. Howson (1997)
15. 5/3 Current Reforms and Stat Activism: Practicing our skills on some well-known papers
   Final Paper
Categories: Announcement, new course | 2 Comments

Where Are Fisher, Neyman, Pearson in 1919? Excursion 3 Tour I

We had a good group zooming into the first half of my seminar on March 1. I’m grateful to them for their interest. They (and anyone else who cares to) are invited to post questions for me, or other thoughts, using the comments to this post. Any new people who want to observe the March 15 session (on statistical debates in particle physics) should write to me. March 22 and 29 will have Aris Spanos and Richard Morey as guest speakers, respectively. The syllabus is here, and the questions/exercises over spring break are here.

The reading from this session is from Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (Mayo, CUP, 2018)

D. Mayo

Tour I Ingenious and Severe Tests

[T]he impressive thing about [the 1919 tests of Einstein’s theory of gravity] is the risk involved in a prediction of this kind. If observation shows that the predicted effect is definitely absent, then the theory is simply refuted.The theory is incompatible with certain possible results of observation – in fact with results which everybody before Einstein would have expected. This is quite different from the situation I have previously described, [where] . . . it was practically impossible to describe any human behavior that might not be claimed to be a verification of these [psychological] theories. (Popper 1962, p. 36)

Mayo 2018, CUP

The 1919 eclipse experiments opened Popper’ s eyes to what made Einstein’ s theory so different from other revolutionary theories of the day: Einstein was prepared to subject his theory to risky tests.[1] Einstein was eager to galvanize scientists to test his theory of gravity, knowing the solar eclipse was coming up on May 29, 1919. Leading the expedition to test GTR was a perfect opportunity for Sir Arthur Eddington, a devout follower of Einstein as well as a devout Quaker and conscientious objector. Fearing “ a scandal if one of its young stars went to jail as a conscientious objector,” officials at Cambridge argued that Eddington couldn’ t very well be allowed to go off to war when the country needed him to prepare the journey to test Einstein’ s predicted light deflection (Kaku 2005, p. 113).

The museum ramps up from Popper through a gallery on “ Data Analysis in the 1919 Eclipse” (Section 3.1) which then leads to the main gallery on origins of statistical tests (Section 3.2). Here’ s our Museum Guide:

According to Einstein’ s theory of gravitation, to an observer on earth, light passing near the sun is deflected by an angle, λ , reaching its maximum of 1.75″ for light just grazing the sun, but the light deflection would be undetectable on earth with the instruments available in 1919. Although the light deflection of stars near the sun (approximately1 second of arc) would be detectable, the sun’ s glare renders such stars invisible, save during a total eclipse, which “ by strange good fortune” would occur on May 29, 1919 (Eddington [1920] 1987, p. 113).

There were three hypotheses for which “ it was especially desired to discriminate between” (Dyson et al. 1920 p. 291). Each is a statement about a parameter, the deflection of light at the limb of the sun (in arc seconds): λ = 0″ (no deflection), λ = 0.87″ (Newton), λ = 1.75″ (Einstein). The Newtonian predicted deflection stems from assuming light has mass and follows Newton’ s Law of Gravity. The difference in statistical prediction masks the deep theoretical differences in how each explains gravitational phenomena. Newtonian gravitation describes a force of attraction between two bodies; while for Einstein gravitational effects are actually the result of the curvature of spacetime. A gravitating body like the sun distorts its surrounding spacetime, and other bodies are reacting to those distortions.

Where Are Some of the Members of Our Statistical Cast of Characters in 1919? In 1919, Fisher had just accepted a job as a statistician at Rothamsted Experimental Station. He preferred this temporary slot to a more secure offer by Karl Pearson (KP), which had so many strings attached – requiring KP to approve everything Fisher taught or published – that Joan Fisher Box writes: After years during which Fisher “ had been rather consistently snubbed” by KP, “It seemed that the lover was at last to be admitted to his lady’ s court – on conditions that he first submit to castration” (J. Box 1978, p. 61). Fisher had already challenged the old guard. Whereas KP, after working on the problem for over 20 years, had only approximated “the first two moments of the sample correlation coefficient; Fisher derived the relevant distribution, not just the first two moments” in 1915 (Spanos 2013a). Unable to fight in WWI due to poor eyesight, Fisher felt that becoming a subsistence farmer during the war, making food coupons unnecessary, was the best way for him to exercise his patriotic duty.

In 1919, Neyman is living a hardscrabble life in a land alternately part of Russia or Poland, while the civil war between Reds and Whites is raging. “It was in the course of selling matches for food” (C. Reid 1998, p. 31) that Neyman was first imprisoned (for a few days) in 1919. Describing life amongst “roaming bands of anarchists, epidemics” (ibid., p. 32), Neyman tells us,“existence” was the primary concern (ibid., p. 31). With little academic work in statistics, and “ since no one in Poland was able to gauge the importance of his statistical work (he was ‘sui generis,’ as he later described himself)” (Lehmann 1994, p. 398), Polish authorities sent him to University College in London in 1925/1926 to get the great Karl Pearson’ s assessment. Neyman and E. Pearson begin work together in 1926. Egon Pearson, son of Karl, gets his B.A. in 1919, and begins studies at Cambridge the next year, including a course by Eddington on the theory of errors. Egon is shy and intimidated, reticent and diffi dent, living in the shadow of his eminent father, whom he gradually starts to question after Fisher’ s criticisms. He describes the psychological crisis he’ s going through at the time Neyman arrives in London: “ I was torn between conflicting emotions: a. finding it difficult to understand R.A.F., b. hating [Fisher] for his attacks on my paternal ‘ god,’ c. realizing that in some things at least he was right” (C. Reid 1998, p. 56). As far as appearances amongst the statistical cast: there are the two Pearsons: tall, Edwardian, genteel; there’ s hardscrabble Neyman with his strong Polish accent and small, toothbrush mustache; and Fisher: short, bearded, very thick glasses, pipe, and eight children. Let’ s go back to 1919, which saw Albert Einstein go from being a little known German scientist to becoming an international celebrity.

  1. You will recognize the above as echoing Popperian “theoretical novelty” – Popper developed it to fit the Einstein test.

…To read further, see Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (CUP, 2018)

Where you are in the journey:

Excursion 3: Statistical Tests and Scientific Inference

Tour I Ingenious and Severe Tests                                             119


3.1 Statistical Inference and Sexy Science: The 1919
Eclipse Test                                                                                    121

3.2 N-P Tests: An Episode in Anglo-Polish Collaboration              131

3.3 How to Do All N-P Tests D (and more) While
a Member of the Fisherian Tribe                                                   146
(we only covered portions of this)

  • All excerpts and mementos (until Nov. 17, 2018) are here.
  • The full Itinerary is here.
Categories: Phil 6014, SIST | Leave a comment

Happy Birthday R.A. Fisher: “Statistical methods and Scientific Induction” with replies by Neyman and E.S. Pearson

17 Feb 1890-29 July 1962

Today is R.A. Fisher’s birthday! I am reblogging what I call the “Triad”–an exchange between  Fisher, Neyman and Pearson (N-P) published 20 years after the Fisher-Neyman break-up. My seminar on PhilStat is studying these this week, so it’s timely. While my favorite is still the reply by E.S. Pearson, which alone should have shattered Fisher’s allegations that N-P “reinterpret” tests of significance as “some kind of acceptance procedure”, all three are chock full of gems for different reasons. They are short and worth rereading. Neyman’s article pulls back the cover on what is really behind Fisher’s over-the-top polemics, what with Russian 5-year plans and commercialism in the U.S. Not only is Fisher jealous that N-P tests came to overshadow “his” tests, he is furious at Neyman for driving home the fact that Fisher’s fiducial approach had been shown to be inconsistent (by others). The flaw is illustrated by Neyman in his portion of the triad. I discuss this briefly in my Philosophy of Science Association paper from a few months ago (slides are here*).Further details may be found in my book, SIST (2018) especially pp 388-392 linked to here. It speaks to a common fallacy seen every day in interpreting confidence intervals. As for Neyman’s “behaviorism”, Pearson’s last sentence is revealing.

HAPPY BIRTHDAY R.A. FISHER! Continue reading

Categories: E.S. Pearson, Fisher, Neyman, phil/history of stat | Leave a comment

Popper, Falsification and Pseudoscience (Notes from my philstat seminar)

My Phil Stat seminar has been meeting for 4 weeks now, and we’re soon to experiment with a small group of outside participants zooming in (write to us, if you are interested in joining us). I’ve been so busy with the seminar that I haven’t blogged. Have you been following? All the materials are on a continually updated syllabus on this blog (SYLLABUS). We’re up to Excursion 2, Tour II.

Last week, we did something unusual: we read from Popper’s Conjectures and Refutations. I wanted to do this because scientists often appeal to distorted and unsophisticated accounts of Popper, especially in discussing falsification, and what demarcates good science from poor science. While I don’t think Popper made good on his most winning slogans, he gives us many seminal launching-off points for improved accounts of falsification, induction, corroboration, and demarcation. Continue reading

Categories: highly probable vs highly probed, science vs pseudoscience, Statistical Inference as Severe Testing | Leave a comment

I’m teaching a New Intro to PhilStat Course Starting Wednesday:

Ship StatInfasst (Statistical Inference as Severe Testing: SIST) will set sail on Wednesday January 18 when I begin a weekly seminar on the Philosophy of Inductive-statistical inference. I’m planning to write a new edition and/or companion to SIST (Mayo 2018, CUP), so it will be good to retrace the journey. I’m not requiring a statistics or philosophy background. All materials will be on this blog, and around halfway through there may be an opportunity to zoom, if there’s interest. Continue reading

Categories: Announcement, new course | 2 Comments

The First 2023 Act of Stat Activist Watch: Statistics ‘for the people’

One of the central roles I proposed for “stat activists” (after our recent workshop, The Statistics Wars and Their Casualties) is to critically scrutinize mistaken claims about leading statistical methods–especially when such claims are put forward as permissible viewpoints to help “the people” assess methods in an unbiased manner. The first act of 2023 under this umbrella concerns an article put forward as “statistics for the people” in a journal of radiation oncology. We are talking here about recommendations for analyzing data for treating cancer!  Put forward as a fair-minded, or at least an informative, comparison of Bayesian vs frequentist methods, I find it to be little more than an advertisement for subjective Bayesian methods in favor of a caricature of frequentist error statistical methods. The journal’s “statistics for the people” section would benefit from a full-blown article on frequentist error statistical methods–not just the letter of ours they recently published–but I’m grateful to Chowdhry and other colleagues who joined me in this effort. You will find our letter below, followed by the authors’ response. You can also find a link to their original “statistics for the people” article in the references. Let me admit right off that my criticisms are a bit stronger than my co-authors. Continue reading

Categories: stat activist watch 2023, statistical significance tests | 2 Comments

Midnight With Birnbaum: Happy New Year 2023!


For the last three years, unlike the previous 10 years that I’ve been blogging, it was not feasible to actually revisit that spot in the road, looking to get into a strange-looking taxi, to head to “Midnight With Birnbaum”.  But this year I will, and I’m about to leave at 10pm. (The pic on the left is the only blurry image I have of the club I’m taken to.) My book Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (CUP, 2018)  doesn’t include the argument from my article in Statistical Science (“On the Birnbaum Argument for the Strong Likelihood Principle”), but you can read it at that link along with commentaries by A. P. David, Michael Evans, Martin and Liu, D. A. S. Fraser, Jan Hannig, and Jan Bjornstad. David Cox, who very sadly did in January 2022, is the one who encouraged me to write and publish it. (The first David R. Cox Foundations of Statistics Prize will be awarded at the JSM 2023.) The (Strong) Likelihood Principle (LP or SLP) remains at the heart of many of the criticisms of Neyman-Pearson (N-P) statistics and of error statistics in general.  Continue reading

Categories: Likelihood Principle, optional stopping, P-value | Leave a comment


Below are the videos and slides from the 7 talks from Session 3 and Session 4 of our workshop The Statistics Wars and Their Casualties held on December 1 & 8, 2022. Session 3 speakers were: Daniele Fanelli (London School of Economics and Political Science), Stephan Guttinger (University of Exeter), and David Hand (Imperial College London).  Session 4 speakers were: Jon Williamson (University of Kent),  Margherita Harris  (London School of Economics and Political Science), Aris Spanos (Virginia Tech), and Uri Simonsohn (Esade Ramon Llull University). Abstracts can be found here. In addition to the talks, you’ll find (1) a Recap of recaps at the beginning of Session 3 that provides a summary of Sessions 1 & 2, and (2) Mayo’s (5 minute) introduction to the final discussion: “Where do we go from here (Part ii)”at the end of Session 4.

The videos & slides from Sessions 1 & 2 can be found on this post.

Readers are welcome to use the comments section on the PhilStatWars.com workshop blog post here to make constructive comments or to ask questions of the speakers. If you’re asking a question, indicate to which speaker(s) it is directed. We will leave it to speakers to respond. Thank you! Continue reading

Categories: Error Statistics | Leave a comment

Slides from PSA22 symposium: Multiplicity, Data-Dredging, and Error Control


Below are slides from 4 of the talks given in our Philosophy of Science Association (PSA) session from last month: the PSA 22 Symposium: Multiplicity, Data-Dredging, and Error Control. It was held in Pittsburgh on November 13, 2022. I will write some reflections in the “comments” to this post. I invite your constructive comments there as well. Continue reading

Categories: data dredging, multiplicity, PSA | 1 Comment

Final Session: The Statistics Wars and Their Casualties: 8 December, Session 4

Thursday, December 8 will be the Final Session (Session 4) of my workshop, The Statistics Wars and Their Casualties. There will be 4 new speakers. It’s not too late to register:

registration form

At the end of this post is “A recap of recaps”, the short video we showed at the beginning of Session 3 last week that summarizes the presentations from Sessions 1 & 2 back in September 22-23. Continue reading

Categories: Announcement, Stistics Wars and Their Casualties Workshop | Leave a comment

SCHEDULE: The Statistics Wars and Their Casualties: 1 Dec & 8 Dec: Sessions 3 & 4

It’s not too late to register for Sessions #3 and #4 of our online Workshop. There will be 7 new (live) speakers and, for the the first time ever, the (short) movie; “The Recap of recaps” will be shown at the start of session #3. registration form

Categories: Announcement, Stistics Wars and Their Casualties Workshop | Leave a comment

Final Sessions: The Statistics Wars and Their Casualties: 1 December and 8 December

The Statistics Wars

and Their Casualties

1 December and 8 December 2022
Sessions #3 and #4

15:00-18:15 pm London Time/10:00am-1:15pm EST
(London School of Economics, CPNSS)
registration form

For slides and videos of Sessions #1 and #2: see the workshop page

1 December

Session 3 (Moderator: Daniël Lakens, Eindhoven University of Technology)


  • “What Happened So Far”: A medley (20 min) of recaps from Sessions 1 & 2: Deborah Mayo (Virginia Tech), Richard Morey (Cardiff), Stephen Senn (Edinburgh), Daniël Lakens (Eindhoven), Christian Hennig (Bologna) & Yoav Benjamini (Tel Aviv).


  • Daniele Fanelli (London School of Economics and Political Science) The neglected importance of complexity in statistics and Metascience  (Abstract)
  • Stephan Guttinger (University of Exeter) What are questionable research practices? (Abstract)
  • David J. Hand (Imperial College, London) What’s the question? (Abstract)


  • Closing Panel: “Where Should Stat Activists Go From Here (Part i)?”: Yoav Benjamini, Daniele Fanelli, Stephan Guttinger, David Hand, Christian Hennig, Daniël Lakens, Deborah Mayo, Richard Morey, Stephen Senn

8 December

Session 4 (Moderator: Deborah Mayo, Virginia Tech)


  • Jon Williamson (University of Kent) Causal inference is not statistical inference (Abstract)
  • Margherita Harris (London School of Economics and Political Science) On Severity, the Weight of Evidence, and the Relationship Between the Two (Abstract)
  • Aris Spanos (Virginia Tech) Revisiting the Two Cultures in Statistical Modeling and Inference as they relate to the Statistics Wars and Their Potential Casualties (Abstract)
  • Uri Simonsohn (Esade Ramon Llull University) Mathematically Elegant Answers to Research Questions No One is Asking (meta-analysis, random effects models, and Bayes factors) (Abstract)


  • Closing Panel: “Where Should Stat Activists Go From Here (Part ii)?”: Workshop Participants: Yoav Benjamini, Alexander Bird, Mark Burgman, Daniele Fanelli, Stephan Guttinger, David Hand, Margherita Harris, Christian Hennig, Daniël Lakens, Deborah Mayo, Richard Morey, Stephen Senn, Uri Simonsohn, Aris Spanos, Jon Williamson


  • DESCRIPTION: While the field of statistics has a long history of passionate foundational controversy, the last decade has, in many ways, been the most dramatic. Misuses of statistics, biasing selection effects, and high-powered methods of big-data analysis, have helped to make it easy to find impressive-looking but spurious results that fail to replicate. As the crisis of replication has spread beyond psychology and social sciences to biomedicine, genomics, machine learning and other fields, the need for critical appraisal of proposed reforms is growing. Many are welcome (transparency about data, eschewing mechanical uses of statistics); some are quite radical. The experts do not agree on the best ways to promote trustworthy results, and these disagreements often reflect philosophical battles–old and new– about the nature of inductive-statistical inference and the roles of probability in statistical inference and modeling. Intermingled in the controversies about evidence are competing social, political, and economic values. If statistical consumers are unaware of assumptions behind rival evidence-policy reforms, they cannot scrutinize the consequences that affect them. What is at stake is a critical standpoint that we may increasingly be in danger of losing. Critically reflecting on proposed reforms and changing standards requires insights from statisticians, philosophers of science, psychologists, journal editors, economists and practitioners from across the natural and social sciences. This workshop will bring together these interdisciplinary insights–from speakers as well as attendees.



  • The Foundation for the Study of Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science (E.R.R.O.R.S.); Centre for Philosophy of Natural and Social Science (CPNSS), London School of Economics; Virginia Tech Department of Philosophy
  • Organizers: D. Mayo, R. Frigg and M. Harris
    (chief logistics and contact person): Jean Miller
    Executive Planning Committee: Y. Benjamini, D. Hand, D. Lakens, S. Senn
Categories: Announcement, Stistics Wars and Their Casualties Workshop | Leave a comment

S. Senn: Lauding Lord (Guest Post)



Stephen Senn
Consultant Statistician
Edinburgh, Scotland

A Diet of Terms

A large university is interested in investigating the effects on the students of the diet provided in the university dining halls and any sex difference in these effects. Various types of data are gathered. In particular, the weight of each student at the time of his arrival in September and their weight the following June are recorded.(P304)

This is how Frederic Lord (1912-2000) introduced the paradox (1) that now bears his name. It is justly famous (or notorious). However, the addition of sex as a factor adds nothing to the essence of the paradox and (in my opinion) merely confuses the issue. Furthermore, studying the effect of diet needs some sort of control. Therefore, I shall consider the paradox in the purer form proposed by Wainer and Brown (2), which was subtly modified by Pearl and Mackenzie in The Book of Why (3) (See pp212-217). Continue reading

Categories: Lord's paradox, S. Senn | 8 Comments

Multiplicity, Data-Dredging, and Error Control Symposium at PSA 2022: Mayo, Thornton, Glymour, Mayo-Wilson, Berger


Some claim that no one attends Sunday morning (9am) sessions at the Philosophy of Science Association. But if you’re attending the PSA (in Pittsburgh), we hope you’ll falsify this supposition and come to hear us (Mayo, Thornton, Glymour, Mayo-Wilson, Berger) wrestle with some rival views on the trenchant problems of multiplicity, data-dredging, and error control. Coffee and donuts to all who show up.

Multiplicity, Data-Dredging, and Error Control
November 13, 9:00 – 11:45 AM
(link to symposium on PSA website)

Speakers: Continue reading

Categories: Announcement, PSA | Leave a comment

Where should stat activists go from here? (part (i))


From what standpoint should we approach the statistics wars? That’s the question from which I launched my presentation at the Statistics Wars and Their Casualties workshop (phil-stat-wars.com). In my view, it should be, not from the standpoint of technical disputes, but from the non-technical standpoint of the skeptical consumer of statistics (see my slides here). What should we do now as regards the controversies and conundrums growing out of the statistics wars? We should not leave off the discussions of our workshop without at least sketching a future program for answering this question. We still have 2 more sessions, December 1 and 8, but I want to prepare us for the final discussions which should look beyond a single workshop. (The slides and videos from the presenters in Sessions 1 and 2 can be found here.)

I will consider three, interrelated, responsibilities and tasks that we can undertake as statistical activist citizens. In so doing I will refer to presentations from the workshop, limiting myself to session #1. (I will add more examples in part (ii) of this post.) Continue reading

Categories: Error Statistics, significance tests, stat wars and their casualties | Leave a comment

My Slides from the workshop: The statistics wars and their casualties


I will be writing some reflections on our two workshop sessions on this blog soon, but for now, here are just the slides I used on Thursday, 22 September. If you wish to ask a question of any of the speakers, use the blogpost at phil-stat-wars.com. The slides from the other speakers will also be up there on Monday.

Deborah G. Mayo’s. Slides from the workshop: The Statistics Wars and Their Casualties, Session 1, on September 22, 2022.

Categories: Error Statistics | 3 Comments

22-23 September final schedule for workshop: The statistics wars and their casualties ONLINE

The Statistics Wars
and Their Casualties

Final Schedule for September 22 & 23 (Workshop Sessions 1 & 2) Continue reading

Categories: Error Statistics | Leave a comment

22-23 Workshop Schedule: The Statistics Wars and Their Casualties: ONLINE

You can still register: https://phil-stat-wars.com/2022/09/19/22-23-september-workshop-schedule-the-statistics-wars-and-their-casualties/ Continue reading

Categories: Error Statistics | Leave a comment

Upcoming Workshop: The Statistics Wars and Their Casualties workshop

The Statistics Wars
and Their Casualties

22-23 September 2022
15:00-18:00 pm London Time*
(London School of Economics, CPNSS)

To register for the  workshop,
please fill out the registration form here.

For schedules and updated details, please see the workshop webpage: phil-stat-wars.com.

*These will be sessions 1 & 2, there will be two more
online sessions (3 & 4) on December 1 & 8.

Continue reading

Categories: Announcement, stat wars and their casualties | 1 Comment

Free access to Statistical Inference as Severe Testing: How to Get Beyond the Stat Wars” (CUP, 2018) for 1 more week


Thanks to CUP, the electronic version of my book, Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (2018), is available for free for one more week (through August 31) at this link:  https://www.cambridge.org/core/books/statistical-inference-as-severe-testing/D9DF409EF568090F3F60407FF2B973B2  Blurbs of the 16 tours in the book may be found here: blurbs of the 16 tours.

Categories: Announcement, SIST | Leave a comment

Blog at WordPress.com.