Posted in participants

Summer Seminar Participant Profiles

Participants in the 2019 Summer Seminar in Philosophy of Statistics

Renée Bolinger, Asst. Professor
Dept of Politics and the Center for Human Values, Princeton University

Lok Chan, Post Doc
Social Science Research Institute, Duke University

Marcello Di Bello
, Asst. Professor
Dept of Philosophy, Lehman College CUNY


John Douard, Appellate Staff Attorney
N.J. Office of the Public Defender


Georgi Gardiner, Junior Research Fellow
St. John’s College, Oxford University
Asst. Professor, Dept. of Philosophy, University of Tennessee


Ruobin (Robin) Gong, Asst. Professor
Department of Statistics and Biostatistics, Rutgers University


Jennifer Juhn, Asst. Professor
Dept of Philosophy, Duke University

Molly Kao, Asst. Professor
Dept. of Philosophy, Université de Montréal


Jesse Krijthe, Post Doc, Data Science
Institute for Computing and Information Sciences, Radboud University


Jonathan Livengood, Assoc. Professor
Dept. of Philosophy, University of Illinois at Urbana-Champaign

Jolynn Pek, Asst. Professor
Dept. of Psychology, Ohio State University


Jonah Schupbach, Assoc. Professor
Dept. of Philosophy, University of Utah


Elay Shech, Asst. Professor
Department of Philosophy, Auburn University


Riet van Bork, Asst. Professor
Department of Psychological Methods, University of Amsterdam

Brian Zaharatos, Director,
Professional MS in Applied Mathematics and Instructor
Dept. of Applied Mathematics, University of Colorado, Boulder

Posted in Uncategorized

Stephen Senn, Special Invited Speaker presentation abstract

Understanding Randomisation

Stephen Senn, Consultant Statistician, Edinburgh

100 years ago, in 1919, Fisher arrived at Rothamsted Agricultural Research Station and began his programme of revolutionising statistics. He realised that it was not enough for the subject of statistics to concern itself with the analysis of data but that it also had to deal with the process of collecting and planning to collect data. Thus, statistics became, under his leadership, a subject not just about analysis of experiments but also about their design.

One of the innovations in design he introduced was randomisation. However, although this has proved to be a practical success in many fields it has become a critical failure amongst many methodologists, in particular, philosophers of science. In my opinion much of the mistrust can be traced to a misunderstanding as to how statistical analysis of randomised experiments proceeds. In this talk I attempt to clear up the misunderstanding and show that many of the criticisms of randomisation turn out to be irrelevant.

Related blogs and articles






Posted in Uncategorized


Drug Stores

CVS:  Next to hotel; 600 University City Blvd Blacksburg (540-951-4911); website.


Farmers Market

Downtown Blacksburg:Wednesdays: Noon-6pm & Saturdays: 9am-2pm (map); (website).


Grocery Stores:

Kroger’s (near your hotel): 24 hours; (540) 951-3045; 903 University City Blvd, Blacksburg, VA 24060; website.

Kroger’s (South Main Street): 24 hours; (540) 953-7004;1322 S Main St., Blacksburg, VA 24060; website.

Oasis World Market: 1411 S Main St, Blacksburg, VA 24060; (540) 953-3950Website

Quaint shops:

Downtown Blacksburg (see here), and recommended by your hotel (here).



First & Main (Blacksburg Mall & Cinema): (423) 246-0009; 1490 S Main Street Blacksburg, VA 24060; website.

New River Valley Mall (Christiansburg Mall & Cinema): website

University Mall (near your hotel):801 University City Blvd, Blacksburg, VA 24060; (540) 552-0882 


Big Box Stores (Christiansburg):

Barnes & Noble: Spradlin Farms, 110 Conston Avenue, Christiansburg, VA 24073; 540-381-4923 website.

Bed Bath & Beyond: New River Valley Mall 135 Shoppers Way Northwest, Christiansburg, VA 24073; Phone(540) 381-7626; website.

Best Buy: 105 Shoppers Way, Christiansburg, VA 24073; (540) 382-9517; website.

Hobby Lobby: 100 Laurel St NE, Christiansburg, VA 24073;(540) 381-6393;  (website)

Lowes: 350 Peppers Ferry Rd NE, Christiansburg, VA 24073; (540) 381-1000website.

Walmart Supercenter: 2400 N Franklin St, Christiansburg, VA 24073; (540) 381-3705; website.

Posted in key articles/chapters

Key Articles/Chapters for the Summer Seminar in Phil Stat

Barnett (1999). Comparative Statistical Inference (Chapter 6: Bayesian Inference), John Wiley & Sons.

Benjamin, Berger, Johannesson et al (2017) Redefine Statistical Significance, Nature Human Behaviour 2, 6-10.

Berger, J. (2003). Could Fisher, Jeffreys and Neyman have Agreed on Testing?  Stat Sci 18: 1-12.

Berger, J. (2006). The Case for Objective Bayesian Analysis and Rejoinder, Bayesian Analysis 1(3), 385–402; 457–64.

Berger, J. & Sellke (1987). Testing a Point Null Hypothesis: The Irreconcilability of P Values and Evidence (with Discussion and Rejoinder), Journal of the American Statistical Association 82(397), 112–22; 135–9.

Bernardo, J. (1997). Non-informative Priors Do Not Exist: A Dialogue with Jose M. Bernardo, Journal of Statistical Planning and Inference 65(1), 159-77.

Casella & R. Berger (1987a). Reconciling Bayesian and Frequentist Evidence in the One-sided Testing Problem, Journal of the American Statistical Association 82(397), 106–11.

Casella, G. and Berger, R. (1987b). Comment on Testing Precise Hypotheses by J. O. Berger and M. Delampady, Statistical Science 2(3), 344–7.

Edwards, Lindman & Savage E, L, & S (1963). Bayesian Statistical Inference for Psychological Research, Psychological Review 70(3), 193–242.

Efron (2013) A 250-Year Argument: Belief, Behavior, and the Bootstrap, Bulletin of the American Mathematical Society 50(1), 126–46. (15)

Fisher (1955), Statistical Methods and Scientific Induction, J R Stat Soc (B) 17: 69-78.

Gelman & Hennig (2017). Beyond Subjective and Objective in Statistics, Journal of the Royal Statistical Society: Series A 180(4), 967–1033.

Gelman & Shalizi (2013). Philosophy and the Practice of Bayesian Statistics (with discussion), Brit. J. Math. Stat. Psy. 66(1): 5-64.

Gigerenzer and Marewski (2017). Surrogate Science: The Idol of a Universal Method for Scientific Inference, Journal of management 41(2), 421-40.

Goodman (1993). P-values, Hypothesis Tests, and Likelihood-Implications for Epidemiology of a Neglected Historical Debate, American Journal of Epidemiology 137(5), 485–96.

Greenland & Poole (2013). Living with P Values: Resurrecting a Bayesian Perspective on Frequentist Statistics and Rejoinder: Living with Statistics in Observational Research, Epidemiology 24(1), 62–8; 73–8. Gelman comment.

Hacking (1980). The Theory of Probable Inference: Neyman, Peirce and Braithwaite, in Mellor, D. (ed.), Science, Belief and Behavior: Essays in Honour of R. B. Braithwaite, Cambridge: Cambridge University Press, pp. 141–60.

Howson (2017). Putting on the Garber Style? Better Not, Philosophy of Science 84(4), 659-76.

Hubbard & Bayarri (2003). Confusion Over Measures of Evidence versus Errors and Rejoinder, The American Statistician 57(3), 171-8; 181-2.

Ioannidis (2005). Why most published research findings are false. PLoS Med 2(8): e124.

Kadane (2016). Beyond Hypothesis Testing, Entropy 18(5), article 199, 1–5.

Kass (2011). Statistical Inference: The Big Picture (with discussion and rejoinder), Statistical Science 26(1), 1–20.

Lakens et al (2018) Justify Your Alpha Nature Human Behaviour 2, 168-71.

Lambert & Black (2012). Learning From Our GWAS Mistakes: From Experimental Design to Scientific Method, Biostatistics 13(2), 195–203.

Levelt Committee, Noort Committee, Drenth Committee (2012). Flawed Science: The Fraudulent Research Practices of Social Psychologist Diederik Stapel, Stapel Investigation: Joint Tilburg/Groningen/Amsterdam investigation of the publications by Mr. Stapel (www.commissielevelt.nl/).

Lindley (2000). The Philosophy of Statistics (with Discussion), Journal of the Royal Statistical Society: Series D 49(3), 293–337.

Neyman (1956). Note on an Article by Sir Ronald Fisher, J R Stat Soc (B) 18: 288-294.

Neyman (1977). Frequentist Probability and Frequentist Statistics, Synthese 36(1), 97–131.

Neyman & Pearson (1933) On the Problem of the Most Efficient Tests of Statistical Hypotheses, Philosophical Transactions of the Royal Society of London Series A 231, 289–337. Reprinted in Joint Statistical Papers, 140–85.

Pearson (1955). Statistical Concepts in Their Relation to Reality, J R Stat Soc (B) 17: 204-207.

Pearson & Chandra Sekar (1936). ‘The Efficiency of Statistical Tools and a Criterion for the Rejection of Outlying Observations’, Biometrika 28 (3/4), 308–20. Reprinted 1966 in The Selected Papers of E. S. Pearson, pp. 118–30.

Popper (1962). Conjectures and Refutations: The Growth of Scientific Knowledge. Basic Books.

Simmons, Nelson & Simonsohn (2012). ‘A 21 word solution’, Dialogue: The Official Newsletter of the Society for Personality and Social Psychology 26(2), 4–7.

A larger list of articles and references here.

Posted in Instructions for Applying


FAQS :(3/3)

(0) What if I must miss the first day or two? We may consider an individual who has a good background and can make her case about promoting the goals of this seminar. (The stipend would be adjusted.) We should have recordings of the main sessions. Write to error@vt.edu and jemille6@vt.edu.

(1) What are the Instructions for Applying? 

These are on the first post of this blog. The Cover sheet contents may be found in the menu of pages at the top of this blog. Please type and pdf your responses.

(2) Will I have to have a background in statistics before the seminar?

The main aim of the seminar is to provide such a background. So, the answer is no. You’ll have a chance to describe your background in your application. Some will have stat and no philo, and we might break out into groups with one group working on philo, the other on stat. You can follow our current graduate Seminar on the drop-down page “PhilStat Spring 19” (at the top of the Error Statistics Philosophy blog).

It’s useful to know some probability, and I find it helpful to watch some of the seminars at the free Khan Academy: AP Statistics. Participants are expected to have read at least 3/4 of SIST (Mayo 2018) in advance so that they can participate and keep up with the discussion in our condensed schedule.

(3) Where is Virginia Tech?

Blacksburg, Virginia–in the beautiful Blue Ridge Mts pictured above.

(4) Who can I contact with questions that aren’t answered here (after December 26)?

We will try to cover all conceivable questions in the instructions here (at least by Jan. 3, 2019). However, if you have other questions, please write to

jemille6@vt.edu (logistics administrator) or error@vt.edu using the following subject for your email: SUMMERSEMINARPHILSTAT in capitals.

*(5) Are graduate students eligible to participate? Advanced graduate students working on a dissertation in this area will be considered. Interested participants who aren’t sure if they are eligible to apply should definitely ask.

*Modification (3/3) A Ph.D student already fully responsible for teaching a course in 2019-20, who can show the goals of our Seminar are furthered by how it will alter the material of that course (& the topics of their dissertation), may be considered,

(6) Are individuals who teach in business, statistics or other fields who feel they would contribute to our mission eligible? Yes. Explain in your application how your project or research would bring our goals to fruition.

(7) What if families require larger dwellings? Blacksburg offers a wide-range of summer rentals of houses and apts. We will do our best to facilitate any participant needing such arrangements.

Posted in Uncategorized

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

Ship StatInfasST

The Statistical Crisis of Science: Where are the Philosophers?

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 medicine, psychology, sociology, economics, and so forth.” (George Barnard 1985, p. 2)

“Relevant clarifications of the nature and roles of statistical evidence in scientific research may well be achieved by bringing to bear in systematic concert the scholarly methods of statisticians, philosophers and historians of science, and substantive scientists…” (Allan Birnbaum 1972, p. 861).

“In the training program for PhD students, the relevant basic principles of philosophy of science, methodology, ethics and statistics that enable the responsible practice of science must be covered.” (p. 57, Committee Investigating fraudulent research practices of social psychologist Diederik Stapel)

I was the lone philosophical observer at a special meeting convened by the American Statistical Association (ASA) in 2015 to construct a non-technical document to guide users of statistical significance tests–one of the most common methods used to distinguish genuine effects from chance variability across a landscape of social, physical and biological sciences.

It was, by the ASA Director’s own description, “historical”, but it was also highly philosophical, and its ramifications are only now being discussed and debated. Today, introspection on statistical methods is rather common due to the “statistical crisis in science”. What is it? In a nutshell: high powered computer methods make it easy to arrive at impressive-looking ‘findings’ that too often disappear when others try to replicate them when hypotheses and data analysis protocols are required to be fixed in advance.

Continue reading “American Phil Assoc Blog: The Stat Crisis of Science: Where are the Philosophers?”

Posted in Current PhilStat Articles

Current (or recent) PhilStat Articles of Relevance: Use comments to add your exs

1  COMPare: Qualitative analysis of researchers’ responses to critical correspondence on a cohort of 58 misreported trials

This is an important and illuminating study on misreporting results of medical trials, along with inaccurate explanations (by authors) of what was done (as a result of letters by Goldacre’s group).


enhanced pdf: