I’m not there. (Several people have asked, I guess because I blogged JSM13.) If you hear of talks (or anecdotes) of interest to error statistics.com, please comment here (or twitter: @learnfromerror)
Announcement
Winner of June Palindrome Contest: Lori Wike
Winner of June 2014 Palindrome Contest: First Second* Time Winner! Lori Wike
*Her April win is here
Palindrome:
Parsec? I overfit omen as Elba sung “I err on! Oh, honor reign!” Usable, sane motif revoices rap.
The requirement: A palindrome with Elba plus overfit. (The optional second word: “average” was not needed to win.)
Bio:
Lori Wike is principal bassoonist of the Utah Symphony and is on the faculty of the University of Utah and Westminster College. She holds a Bachelor of Music degree from the Eastman School of Music and a Master of Arts degree in Comparative Literature from UCIrvine.
Scientism and Statisticism: a conference* (i)
A lot of philosophers and scientists seem to be talking about scientism these days–either championing it or worrying about it. What is it? It’s usually a pejorative term describing an unwarranted deference to the socalled scientific method over and above other methods of inquiry. Some push it as a way to combat postmodernism (is that even still around?) Stephen Pinker gives scientism a positive spin (and even offers it as a cure for the malaise of the humanities!)[1]. Anyway, I’m to talk at a conference on Scientism (*not statisticism, that’s my word) taking place in NYC May 1617. It is organized by Massimo Pigliucci (chair of philosophy at CUNYLehman), who has written quite a lot on the topic in the past few years. Information can be found here. In thinking about scientism for this conference, however, I was immediately struck by this puzzle: Continue reading
Winner of April Palindrome contest: Lori Wike
Winner of April 2014 Palindrome Contest:
Lori Wike
Palindrome:
Pose ad: ‘Elba fallacy amid aged? Amygdala error or real?’ Ad: gym ad? Egad! I may call a fabled Aesop.
The requirement: A palindrome with Elba plus “fallacy” with an optional second word: “error”. A palindrome using both topped an acceptable palindrome using only “fallacy”. All April submissions used both. Other April finalists are here.
Bio:
Lori Wike is principal bassoonist of the Utah Symphony and is on the faculty of the University of Utah and Westminster College. She holds a Bachelor of Music degree from the Eastman School of Music and a Master of Arts degree in Comparative Literature from UCIrvine.
Putting the brakes on the breakthrough: An informal look at the argument for the Likelihood Principle
Friday, May 2, 2014, I will attempt to present my critical analysis of the Birnbaum argument for the (strong) Likelihood Principle, so as to be accessible to a general philosophy audience (flyer below). Can it be done? I don’t know yet, this is a first. It will consist of:
 Example 1: Trying and Trying Again: Optional stopping
 Example 2: Two instruments with different precisions
[you shouldn’t get credit (or blame) for something you didn’t do]  The Breakthough: Birnbaumization
 Imaginary dialogue with Allan Birnbaum
The full paper is here. My discussion takes several pieces a reader can explore further by searching this blog (e.g., under SLP, brakes e.g., here, Birnbaum, optional stopping). I will post slides afterwards.
Phil 6334 Visitor: S. Stanley Young, “Statistics and Scientific Integrity”
We are pleased to announce our guest speaker at Thursday’s seminar (April 24, 2014): “Statistics and Scientific Integrity”:
S. Stanley Young, PhD
Assistant Director for Bioinformatics
National Institute of Statistical Sciences
Research Triangle Park, NC
Author of ResamplingBased Multiple Testing, Westfall and Young (1993) Wiley.
The main readings for the discussion are:
 Young, S. & Karr, A. (2011). Deming, Data and Observational Studies. Signif. 8 (3), 116–120.
 Begley & Ellis (2012) Raise standards for preclinical cancer research. Nature 483: 531533.
 Ioannidis (2005). Why most published research ﬁndings are false. PLoS Med 2(8): e124.
 Peng, R. D., Dominici, F. & Zeger, S. L. (2006). “Reproducible Epidemiologic Research” American Journal of Epidemiology 163 (9), 783789.
Winner of the March 2014 palindrome contest (rejected post)
Caitlin Parker
Palindrome:Able, we’d well aim on. I bet on a note. Binomial? Lewd. Ew, Elba!
The requirement was: A palindrome with Elba plus Binomial with an optional second word: bet. A palindrome that uses both Binomial and bet topped an acceptable palindrome that only uses Binomial.
Short bio:
Caitlin Parker is a firstyear master’s student in the Philosophy department at Virginia Tech. Though her interests are in philosophy of science and statistics, she also has experience doing psychological research. Continue reading
Cosma Shalizi gets tenure (at last!) (metastat announcement)
News Flash! Congratulations to Cosma Shalizi who announced yesterday that he’d been granted tenure (Statistics, Carnegie Mellon). Cosma is a leading error statistician, a creative polymath and longtime blogger (at ThreeToad sloth). Shalizi wrote an early book review of EGEK (Mayo 1996)* that people still send me from time to time, in case I hadn’t seen it! You can find it on this blog from 2 years ago (posted by Jean Miller). A discussion of a meeting of the minds between Shalizi and Andrew Gelman is here.
*Error and the Growth of Experimental Knowledge.
Winner of the Febrary 2014 palindrome contest (rejected post)
Winner of February 2014 Palindrome Contest
Samuel Dickson
Palindrome:
Rot, Cadet A, I’ve droned! Elba, revile deviant, naïve, deliverable den or deviated actor.
The requirement was: A palindrome with Elba plus deviate with an optional second word: deviant. A palindrome that uses both deviate and deviant tops an acceptable palindrome that only uses deviate.
Bio:
Sam Dickson is a regulatory statistician at U.S. Army Medical Research Institute of Infectious Diseases (USAMRIID) with experience in statistical consulting, specializing in design and analysis of biological and genetics/genomics studies.
Statement:
“It’s great to get a chance to exercise the mind with something other than statistics, though putting words together to make a palindrome is a puzzle very similar to designing an experiment that answers the right question. Thank you for hosting this contest!”
Choice of book:
Principles of Applied Statistics (D. R. Cox and C. A. Donnelly 2011, Cambridge: Cambridge University Press)
Congratulations, Sam! I hope that your opting to do two words (plus Elba) means we can go back to the tougher standard for palindromes, but I’d just as soon raise the level of competence for several months more (sticking to one word).
Phil6334 Statistical Snow Sculpture
No Seminar. Blizzard.
BOSTON COLLOQUIUM FOR PHILOSOPHY OF SCIENCE: Revisiting the Foundations of Statistics
BOSTON COLLOQUIUM FOR PHILOSOPHY OF SCIENCE
2013–2014
54th Annual Program
Download the 54th Annual Program
REVISITING THE FOUNDATIONS OF STATISTICS IN THE ERA OF BIG DATA: SCALING UP TO MEET THE CHALLENGE
Cosponsored by the Department of Mathematics & Statistics at Boston University.
Friday, February 21, 2014
10 a.m. – 5:30 p.m.
Photonics Center, 9th Floor Colloquium Room (Rm 906)
8 St. Mary’s Street
10 a.m.–noon
 Computational Challenges in Genomic Medicine
Jill Mesirov Computational Biology and Bioinformatics, Broad Institute  Selection, Significance, and Signification: Issues in High Energy Physics
Kent Staley Philosophy, Saint Louis University
1:30–5:30 p.m.
 MultiResolution Inference: An Engineering (Engineered?) Foundation of Statistical Inference
XiaoLi Meng Statistics, Harvard University  Is the Philosophy of Probabilism an Obstacle to Statistical Fraud Busting?
Deborah Mayo Philosophy, Virginia Tech  Targeted Learning from Big Data
Mark van der Laan Biostatistics and Statistics, UC Berkeley
Panel Discussion
Winner of the January 2014 palindrome contest (rejected post)
Winner of the January 2014 Palindrome Context
Karthik Durvasula
Visiting Assistant Professor in Phonology & Phonetics at Michigan State University
Palindrome: Test’s optimal? Agreed! Able to honor? O no! Hot Elba deer gala. MITpost set.
The requirement was: A palindrome with “optimal” and “Elba”.
Bio: I’m a Visiting Assistant Professor in Phonology & Phonetics at Michigan State University. My work primarily deals with probing people’s subconscious knowledge of (abstract) sound patterns. Recently, I have been working on auditory illusions that stem from the bias that such subconscious knowledge introduces.
Statement: “Trying to get a palindrome that was at least partially meaningful was fun and challenging. Plus I get an awesome book for my efforts. What more could a guy ask for! I also want to thank Mayo for being excellent about email correspondence, and answering my (sometimes silly) questions tirelessly.”
Book choice: EGEK 1996! :)
[i.e.,Mayo (1996): "Error and the Growth of Experimental Knowledge"]
CONGRATULATIONS! And thanks so much for your interest!
February contest: Elba plus deviate (deviation)*
New Rule: Using both deviate and deviant tops an acceptable palindrome that only uses deviate (but can earn 1/2 prize voucher for doubling on another month).
Phil6334: “Philosophy of Statistical Inference and Modeling” New Course: Spring 2014: Mayo and Spanos: (Virginia Tech) UPDATE: JAN 21
FURTHER UPDATED: New course for Spring 2014: Thurs 3:306:15 (Randolph 209)
first installment 6334 syllabus_SYLLABUS (first) Phil 6334: Philosophy of Statistical Inference and Modeling
D. Mayo and A. Spanos
Contact: error@vt.edu
This new course, to be jointly taught by Professors D. Mayo (Philosophy) and A. Spanos (Economics) will provide an introductory, indepth introduction to graduate level research in philosophy of inductivestatistical inference and probabilistic methods of evidence (a branch of formal epistemology). We explore philosophical problems of confirmation and induction, the philosophy and history of frequentist and Bayesian approaches, and key foundational controversies surrounding tools of statistical data analytics, modeling and hypothesis testing in the natural and social sciences, and in evidencebased policy.
We now have some tentative topics and dates:
1. 1/23  Introduction to the Course: 4 waves of controversy in the philosophy of statistics 
2. 1/30  How to tell what’s true about statistical inference: Probabilism, performance and probativeness 
3. 2/6  Induction and Confirmation: Formal Epistemology 
4. 2/13  Induction, falsification, severe tests: Popper and Beyond 
5. 2/20  Statistical models and estimation: the Basics 
6. 2/27  Fundamentals of significance tests and severe testing 
7. 3/6  Five sigma and the Higgs Boson discovery Is it “bad science”? 
SPRING BREAK Statistical Exercises While Sunning  
8. 3/20  Fraudbusting and Scapegoating: Replicability and big data: are most scientific results false? 
9. 3/27  How can we test the assumptions of statistical models? All models are false; no methods are objective: Philosophical problems of misspecification testing: Spanos method 
10. 4/3  Fundamentals of Statistical Testing: Family Feuds and 70 years of controversy 
11. 4/10  Error Statistical Philosophy: Highly Probable vs Highly Probed Some howlers of testing 
12. 4/17  What ever happened to Bayesian Philosophical Foundations? Dutch books etc. Fundamental of Bayesian statistics 
13. 4/24  Bayesianfrequentist reconciliations, unifications, and OBayesians 
14. 5/1  Overview: Answering the critics: Should statistical philosophy be divorced from methodology? 
(15. TBA)  Topic to be chosen (Resampling statistics and new journal policies? Likelihood principle) 
Interested in attending? E.R.R.O.R.S.* can fund travel (presumably driving) and provide accommodation for Thurs. night in a conference lodge in Blacksburg for a few people through (or part of) the semester. If interested, write ASAP for details (with a brief description of your interest and background) to error@vt.edu. (Several people asked about longdistance hookups: We will try to provide some sessions by Skype, and will put each of the seminar items here (also check the Phil6334 page on this blog).
A sample of questions we consider*:
 What makes an inquiry scientific? objective? When are we warranted in generalizing from data?
 What is the “traditional problem of induction”? Is it really insoluble? Does it matter in practice?
 What is the role of probability in uncertain inference? (to assign degrees of confirmation or belief? to characterize the reliability of test procedures?) 3P’s: Probabilism, performance and probativeness
 What is probability? Random variables? Estimates? What is the relevance of longrun error probabilities for inductive inference in science?
 What did Popper really say about severe testing, induction, falsification? Is it time for a new definition of pseudoscience?
 Confirmation and falsification: Carnap and Popper, paradoxes of confirmation; contemporary formal epistemology
 What is the current state of play in the “statistical wars” e.g., between frequentists, likelihoodists, and (subjective vs. “nonsubjective”) Bayesians?
 How should one specify and interpret pvalues, type I and II errors, confidence levels? Can one tell the truth (and avoid fallacies) with statistics? Do the “reformers” themselves need reform?
 Is it unscientific (ad hoc, degenerating) to use the same data both in constructing and testing hypotheses? When and why?
 Is it possible to test assumptions of statistical models without circularity?
 Is the new research on “replicability” wellfounded, or an erroneous use of screening statistics for longrun performance?
 Should randomized studies be the “gold standard” for “evidencebased” science and policy?
 What’s the problem with big data: cherrypicking, data mining, multiple testing
 The many faces of Bayesian statistics: Can there be uninformative prior probabilities? (No) Principles of indifference over the years
 Statistical fraudbusting: psychology, economics, evidencebased policy
 Applied controversies (selected): Higgs experiments, climate modeling, social psychology, econometric modeling, development economic
D. Mayo (books):
How to Tell What’s True About Statistical Inference, (Cambridge, in progress).
Error and the Growth of Experimental Knowledge, Chicago: Chicago University Press, 1996. (Winner of 1998 Lakatos Prize).
Acceptable Evidence: Science and Values in Risk Management, coedited with Rachelle Hollander, New York: Oxford University Press, 1994.
Aris Spanos (books):
Probability Theory and Statistical Inference, Cambridge, 1999.
Statistical Foundations of Econometric Modeling, Cambridge, 1986.
Joint (books): Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability and the Objectivity and Rationality of Science, D. Mayo & A. Spanos (eds.), Cambridge: Cambridge University Press, 2010. [The book includes both papers and exchanges between Mayo and A. Chalmers, A. Musgrave, P. Achinstein, J. Worrall, C. Glymour, A. Spanos, and joint papers with Mayo and Sir David Cox].
“Philosophy of Statistical Inference and Modeling” New Course: Spring 2014: Mayo and Spanos: (Virginia Tech)
New course for Spring 2014: Thursday 3:306:15
Phil 6334: Philosophy of Statistical Inference and Modeling
D. Mayo and A. Spanos
Contact: error@vt.edu
This new course, to be jointly taught by Professors D. Mayo (Philosophy) and A. Spanos (Economics) will provide an introductory, indepth introduction to graduate level research in philosophy of inductivestatistical inference and probabilistic methods of evidence (a branch of formal epistemology). We explore philosophical problems of confirmation and induction, the philosophy and history of frequentist and Bayesian approaches, and key foundational controversies surrounding tools of statistical data analytics, modeling and hypothesis testing in the natural and social sciences, and in evidencebased policy.
A sample of questions we consider*:
 What makes an inquiry scientific? objective? When are we warranted in generalizing from data?
 What is the “traditional problem of induction”? Is it really insoluble? Does it matter in practice?
 What is the role of probability in uncertain inference? (to assign degrees of confirmation or belief? to characterize the reliability of test procedures?) 3P’s: Probabilism, performance and probativeness
 What is probability? Random variables? Estimates? What is the relevance of longrun error probabilities for inductive inference in science?
 What did Popper really say about severe testing, induction, falsification? Is it time for a new definition of pseudoscience?
 Confirmation and falsification: Carnap and Popper, paradoxes of confirmation; contemporary formal epistemology
 What is the current state of play in the “statistical wars” e.g., between frequentists, likelihoodists, and (subjective vs. “nonsubjective”) Bayesians?
 How should one specify and interpret pvalues, type I and II errors, confidence levels? Can one tell the truth (and avoid fallacies) with statistics? Do the “reformers” themselves need reform?
 Is it unscientific (ad hoc, degenerating) to use the same data both in constructing and testing hypotheses? When and why?
 Is it possible to test assumptions of statistical models without circularity?
 Is the new research on “replicability” wellfounded, or an erroneous use of screening statistics for longrun performance?
 Should randomized studies be the “gold standard” for “evidencebased” science and policy?
 What’s the problem with big data: cherrypicking, data mining, multiple testing
 The many faces of Bayesian statistics: Can there be uninformative prior probabilities? (No) Principles of indifference over the years
 Statistical fraudbusting: psychology, economics, evidencebased policy
 Applied controversies (selected): Higgs experiments, climate modeling, social psychology, econometric modeling, development economic
Interested in attending? E.R.R.O.R.S.* can fund travel (presumably driving) and provide lodging for Thurs. night in a conference lodge in Blacksburg for a few people through (or part of) the semester. Topics will be posted over the next week, but if you might be interested, write ASAP for details (with a brief description of your interest and background) to error@vt.edu.
*This course will be a brand new version of related seminar we’ve led in the past, so we don’t have the syllabus set yet. We’re going to try something different this time. I’ll be updating in subsequent installments to the blog.
Dates: January 23, 30; February 6, 13, 20, 27; March 6, [March 816 break], 20, 27; April 3,10, 17, 24; May 1
D. Mayo (books):
How to Tell What’s True About Statistical Inference, (Cambridge, in progress).
Error and the Growth of Experimental Knowledge, Chicago: Chicago University Press, 1996. (Winner of 1998 Lakatos Prize).
Acceptable Evidence: Science and Values in Risk Management, coedited with Rachelle Hollander, New York: Oxford University Press, 1994.
Aris Spanos (books):
Probability Theory and Statistical Inference, Cambridge, 1999.
Statistical Foundations of Econometric Modeling, Cambridge, 1986.
Joint (books): Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability and the Objectivity and Rationality of Science, D. Mayo & A. Spanos (eds.), Cambridge: Cambridge University Press, 2010. [The book includes both papers and exchanges between Mayo and A. Chalmers, A. Musgrave, P. Achinstein, J. Worrall, C. Glymour, A. Spanos, and joint papers with Mayo and Sir David Cox].
FDA’S New Pharmacovigilance

Blog Contents: August 2013
August 2013
(8/1) Blogging (flogging?) the SLP: Response to Reply Xi’an Robert
(8/5) At the JSM: 2013 International Year of Statistics
(8/6) What did Nate Silver just say? Blogging the JSM
(8/9) 11^{th} bullet, multiple choice question, and last thoughts on the JSM
(8/11) E.S. Pearson: “Ideas came into my head as I sat on a gate overlooking an experimental blackcurrant plot”
(8/13) Blogging E.S. Pearson’s Statistical Philosophy
(8/15) A. Spanos: Egon Pearson’s Neglected Contributions to Statistics
(8/17) Gandenberger: How to Do Philosophy That Matters (guest post)
(8/21) Blog contents: July, 2013
(8/22) PhilStock: Flash Freeze
(8/22) A critical look at “critical thinking”: deduction and induction
(8/28) Is being lonely unnatural for slim particles? A statistical argument
(8/31) Overheard at the comedy hour at the Bayesian retreat2 years on
Palindrome “contest” contest
Want to win one of these books? You may not have noticed that since May, the palindrome rules have gotten trivially easy. So since it’s Saturday night, and I’m giving a time extension to 14 July – Le Quatorze juillet—have some fun coming up with a palindrome. It only needs to include “Elba” and the word “contest”. For full bibiographies and complete rules, see palindrome page:
.Send your candidates to me at error@vt.edu. One of the winners under the older, much harder, rules is here.
Previous palindrome contests included:
runs test, omnibus, cycle, dominate, editor, data, Model, sample, random, probable, Bayes, confident, likely, error, decision, variable, integrate, maximal, median (comedian), interpret, action, code, predict, luck, assess, model, simple, null, bootstrap,minimum, wrong, prefer, dogma, (s)exist, email
with variations.
Schedule for Ontology & Methodology, 2013
May 4 (Saturday):
8:309:00: Pastries & Coffee (Continental Breakfast) outside of Pamplin 2030
MORNING SESSIONS:
9:009:15—Welcome talk
9:1510:00 Ruetsche: “Method, Metaphysics, and Quantum Theory”
10:0010:25: Discussion
10:2510:40 coffee break
10:4011:05 Shech, “Phase Transitions, Ontology and Earman’s Sound Principle”
11:0511:20: Discussion
11:2012:05 GodfreySmith, “Evolution and Agency: A Case Study in Ontology and Methodology”
12:0512:30: Discussion
12:301:30 Box Lunch
AFTERNOON SESSIONS: Continue reading
Coming up: December UPhil Contributions….
Dear Reader: You were probably* wondering about the December UPhils (blogging the strong likelihood principle (SLP)). They will be posted, singly or in pairs, over the next few blog entries. Here is the initial call, and the extension. The details of the specific UPhil may be found here, but also look at the post from my 28 Nov. seminar at the London School of Economics (LSE), which was on the SLP. Posts were to be in relation to either the guest graduate student post by Gandenberger, and/or my discussion/argument and reactions to it. Earlier UPhils may be found here; and more by searching this blog. “UPhil” is short for “you ‘philosophize”.
If you have ideas for future “UPhils,” post them as comments to this blog or send them to error@vt.edu.
*This is how I see “probability” mainly used in ordinary English, namely as expressing something like “here’s a pure guess made without evidence or with little evidence,” be it sarcastic or quite genuine.