Unlike in the past 9 years since I’ve been blogging, I can’t revisit that spot in the road outside the Elbar Room, looking to get into a strange-looking taxi, to head to “Midnight With Birnbaum”. Because of the pandemic, I refuse to go out this New Year’s Eve, so the best I can hope for is a zoom link that will take me to a hypothetical party with him. (The pic on the left is the only blurry image I have of the club I’m taken to.) I just keep watching my email, to see if a zoom link arrives. My book *Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (STINT 2018)* doesn’t rehearse the argument from my Birnbaum article, but there’s much in it that I’d like to discuss with him. The (Strong) Likelihood Principle–whether or not it is named–remains at the heart of many of the criticisms of Neyman-Pearson (N-P) statistics and statistical significance testing in general. Let’s hope that in 2021 the American Statistical Association 9ASA) will finally reveal the recommendations from the ASA Task Force on Statistical Significance and Replicability that the ASA Board itself created one year ago. They completed their recommendations early–back at the end of July 2020–but no response from the ASA has been forthcoming (to my knowledge). As Birnbaum insisted, the “confidence concept” is the “one rock in a shifting scene” of statistical foundations, insofar as there’s interest in controlling the frequency of erroneous interpretations of data. (See my rejoinder.) Birnbaum bemoaned the lack of an explicit evidential interpretation of N-P methods. I purport to give one in SIST 2018. Maybe it will come to fruition in 2021? Anyway, I was just sent an internet link–but it’s not zoom, not Skype, not Webinex, or anything I’ve ever seen before….no time to describe it now, but I’m recording and the rest of the transcript is live; this year there are some new, relevant additions. Happy New Year! Continue reading

# strong likelihood principle

## Midnight With Birnbaum (Remote, Virtual Happy New Year 2020)!

## Cox’s (1958) Chestnut: You should not get credit (or blame) for something you didn’t do

Just as you keep up your physical exercise during the pandemic (*sure*), you want to keep up with mental gymnastics too. With that goal in mind, and given we’re just a few days from the New Year (and given especially my promised presentation for January 7), here’s one of the two simple examples that will limber you up for the puzzle to ensue. It’s the famous weighing machine example from Sir David Cox (1958)[1]. It is one of the “chestnuts” in the museum exhibits of “chestnuts and howlers” in Excursion 3 (Tour II) of my book *Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars* (SIST, 2018). So block everything else out for a few minutes and consider 3 pages from SIST … Continue reading

## Birthday of Allan Birnbaum: Foundations of Probability and Statistics (27 May 1923 – 1 July 1976)

** Today is Allan Birnbaum’s birthday. In honor of his birthday, I’m posting the articles in the Synthese volume that was dedicated to his memory in 1977. The editors describe it as their way of “paying homage to Professor Birnbaum’s penetrating and stimulating work on the foundations of statistics”. I had posted the volume before, but there are several articles that are very worth rereading. I paste a few snippets from the articles by Giere and Birnbaum. If you’re interested in statistical foundations, and are unfamiliar with Birnbaum, here’s a chance to catch up. (Even if you are, you may be unaware of some of these key papers.)** Continue reading

## Midnight With Birnbaum (Happy New Year 2019)!

Just as in the past 8 years since I’ve been blogging, I revisit that spot in the road at 9p.m., just outside the Elbar Room, look to get into a strange-looking taxi, to head to “Midnight With Birnbaum”. (The pic on the left is the only blurry image I have of the club I’m taken to.) I wonder if the car will come for me this year, as I wait out in the cold, now that *Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (STINT 2018)* has been out over a year. STINT doesn’t rehearse the argument from my Birnbaum article, but there’s much in it that I’d like to discuss with him. The (Strong) Likelihood Principle–whether or not it is named–remains at the heart of many of the criticisms of Neyman-Pearson (N-P) statistics (and cognate methods). 2019 was the 61th birthday of Cox’s “weighing machine” example, which was the basis of Birnbaum’s attempted proof. Yet as Birnbaum insisted, the “confidence concept” is the “one rock in a shifting scene” of statistical foundations, insofar as there’s interest in controlling the frequency of erroneous interpretations of data. (See my rejoinder.) Birnbaum bemoaned the lack of an explicit evidential interpretation of N-P methods. Maybe in 2020? Anyway, the cab is finally here…the rest is live. Happy New Year! Continue reading

## Cox’s (1958) Chestnut: You shouldn’t get credit (or blame) for something you didn’t do

Just as you regularly keep up your physical exercise during the pandemic (sure), you also want to keep up with brain exercise. Given we’re just a few days from New Year’s eve, and given especially that on January 7 I will attempt (for the first time) a highly informal presentation of a controversial result in statistical foundations), here’s a little 2018 marked 60 years since the famous weighing machine example from Sir David Cox (1958)[1]. it is now 61. It’s one of the “chestnuts” in the exhibits of “chestnuts and howlers” in Excursion 3 (Tour II) of my (still) new book *Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars* (SIST, 2018). It’s especially relevant to take this up now, just before we leave 2019, for reasons that will be revealed over the next day or two. For a sneak preview of those reasons, see the “note to the reader” at the end of this post. So, let’s go back to it, with an excerpt from SIST (pp. 170-173). Continue reading

## Midnight With Birnbaum (Happy New Year 2018)

Just as in the past 7 years since I’ve been blogging, I revisit that spot in the road at 9p.m., just outside the Elbar Room, look to get into a strange-looking taxi, to head to “Midnight With Birnbaum”. (The pic on the left is the only blurry image I have of the club I’m taken to.) I wonder if the car will come for me this year, as I wait out in the cold, now that *Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (STINT)* is out. STINT doesn’t rehearse the argument from my Birnbaum article, but there’s much in it that I’d like to discuss with him. The (Strong) Likelihood Principle–whether or not it is named–remains at the heart of many of the criticisms of Neyman-Pearson (N-P) statistics (and cognate methods). 2018 was the 60th birthday of Cox’s “weighing machine” example, which was the basis of Birnbaum’s attempted proof. Yet as Birnbaum insisted, the “confidence concept” is the “one rock in a shifting scene” of statistical foundations, insofar as there’s interest in controlling the frequency of erroneous interpretations of data. (See my rejoinder.) Birnbaum bemoaned the lack of an explicit evidential interpretation of N-P methods. Maybe in 2019? Anyway, the cab is finally here…the rest is live. Happy New Year! Continue reading

## You Should Be Binge Reading the (Strong) Likelihood Principle

An essential component of inference based on familiar frequentist notions: p-values, significance and confidence levels, is the relevant sampling distribution (hence the term *sampling theory, *or my preferred *error statistics, *as we get error probabilities from the sampling distribution). This feature results in violations of a principle known as the *strong likelihood principle* (SLP). To state the SLP roughly, it asserts that all the evidential import in the data (for parametric inference within a model) resides in the likelihoods. If accepted, it would render error probabilities irrelevant post data.

**SLP** (We often drop the “strong” and just call it the LP. The “weak” LP just boils down to sufficiency)

For any two experiments E

_{1}and E_{2}with different probability models f_{1}, f_{2}, but with the same unknown parameter θ, if outcomesx* andy* (from E_{1}and E_{2}respectively) determine the same (i.e., proportional) likelihood function (f_{1}(x*; θ) = cf_{2}(y*; θ) for all θ), thenx* andy* are inferentially equivalent (for an inference about θ).

(What differentiates the weak and the strong LP is that the weak refers to a single experiment.)

Continue reading

## 60 Years of Cox’s (1958) Chestnut: Excerpt from Excursion 3 Tour II (Mayo 2018, CUP)

2018 marked 60 years since the famous weighing machine example from Sir David Cox (1958)[1]. It’s one of the “chestnuts” in the exhibits of “chestnuts and howlers” in Excursion 3 (Tour II) of my new book *Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars* (SIST). It’s especially relevant to take this up now, just before we leave 2018, for reasons that will be revealed over the next day or two. So, let’s go back to it, with an excerpt from SIST (pp. 170-173).

**Exhibit (vi): Two Measuring Instruments of Different Precisions. ***Did you hear about the frequentist who, knowing she used a scale that’s right only half the time, claimed her method of weighing is right 75% of the time?*

She says, “I flipped a coin to decide whether to use a scale that’s right 100% of the time, or one that’s right only half the time, so, overall, I’m right 75% of the time.” (She wants credit because she could have used a better scale, even knowing she used a lousy one.)

*Basis for the joke: *An N-P test bases error probability on all possible outcomes or measurements that could have occurred in repetitions, but did not. Continue reading

## Midnight With Birnbaum (Happy New Year 2017)

**Just as in the past 6 years since I’ve been blogging, I revisit that spot in the road at 11p.m., just outside the Elbar Room, look to get into a strange-looking taxi, to head to “Midnight With Birnbaum”. (The pic on the left is the only blurry image I have of the club I’m taken to.) I wondered if the car would come for me this year, as I waited out in the cold, given that my Birnbaum article has been out since 2014. The (Strong) Likelihood Principle–whether or not it is named–remains at the heart of many of the criticisms of Neyman-Pearson (N-P) statistics (and cognate methods). 2018 will be the 60th birthday of Cox’s “weighing machine” example, which was the start of Birnbaum’s attempted proof. Yet as Birnbaum insisted, the “confidence concept” is the “one rock in a shifting scene” of statistical foundations, insofar as there’s interest in controlling the frequency of erroneous interpretations of data. (See my rejoinder.) Birnbaum bemoaned the lack of an explicit evidential interpretation of N-P methods. Maybe in 2018? Anyway, the cab is finally here…the rest is live. Happy New Year!** Continue reading

## 60 yrs of Cox’s (1958) weighing machine, & links to binge-read the Likelihood Principle

2018 will mark 60 years since the famous chestnut from Sir David Cox (1958). The example “is now usually called the ‘weighing machine example,’ which draws attention to the need for conditioning, at least in certain types of problems” (Reid 1992, p. 582). When I describe it, you’ll find it hard to believe many regard it as causing an earthquake in statistical foundations, unless you’re already steeped in these matters. A simple version: If half the time I reported my weight from a scale that’s always right, and half the time use a scale that gets it right with probability .5, would you say I’m right with probability ¾? Well, maybe. But suppose you *knew* that this measurement was made with the scale that’s right with probability .5? The overall error probability is scarcely relevant for giving the warrant of the particular measurement, *knowing* which scale was used. So what’s the earthquake? First a bit more on the chestnut. Here’s an excerpt from Cox and Mayo (2010, 295-8): Continue reading

## Allan Birnbaum: Foundations of Probability and Statistics (27 May 1923 – 1 July 1976)

*Today is Allan Birnbaum’s birthday. In honor of his birthday, I’m posting the articles in the Synthese volume that was dedicated to his memory in 1977. The editors describe it as their way of “paying homage to Professor Birnbaum’s penetrating and stimulating work on the foundations of statistics”. I paste a few snippets from the articles by Giere and Birnbaum. If you’re interested in statistical foundations, and are unfamiliar with Birnbaum, here’s a chance to catch up. (Even if you are, you may be unaware of some of these key papers.)*

**HAPPY BIRTHDAY ALLAN!**

*Synthese* Volume 36, No. 1 Sept 1977: *Foundations of Probability and Statistics*, Part I

**Editorial Introduction:**

This special issue of

Syntheseon the foundations of probability and statistics is dedicated to the memory of Professor Allan Birnbaum. Professor Birnbaum’s essay ‘The Neyman-Pearson Theory as Decision Theory; and as Inference Theory; with a Criticism of the Lindley-Savage Argument for Bayesian Theory’ was received by the editors ofSynthesein October, 1975, and a decision was made to publish a special symposium consisting of this paper together with several invited comments and related papers. The sad news about Professor Birnbaum’s death reached us in the summer of 1976, but the editorial project could nevertheless be completed according to the original plan. By publishing this special issue we wish to pay homage to Professor Birnbaum’s penetrating and stimulating work on the foundations of statistics. We are grateful to Professor Ronald Giere who wrote an introductory essay on Professor Birnbaum’s concept of statistical evidence and who compiled a list of Professor Birnbaum’s publications.THE EDITORS

## Cox’s (1958) weighing machine example

A famous chestnut given by Cox (1958) recently came up in conversation. The example “is now usually called the ‘weighing machine example,’ which draws attention to the need for conditioning, at least in certain types of problems” (Reid 1992, p. 582). When I describe it, you’ll find it hard to believe many regard it as causing an earthquake in statistical foundations, unless you’re already steeped in these matters. If half the time I reported my weight from a scale that’s always right, and half the time use a scale that gets it right with probability .5, would you say I’m right with probability ¾? Well, maybe. But suppose you knew that this measurement was made with the scale that’s right with probability .5? The overall error probability is scarcely relevant for giving the warrant of the particular measurement,knowing which scale was used. Continue reading

## Midnight With Birnbaum (Happy New Year 2016)

**Just as in the past 5 years since I’ve been blogging, I revisit that spot in the road at 11p.m., just outside the Elbar Room, get into a strange-looking taxi, and head to “Midnight With Birnbaum”. (The pic on the left is the only blurry image I have of the club I’m taken to.) I wonder if the car will come for me this year, given that my Birnbaum article has been out since 2014… The (Strong) Likelihood Principle–whether or not it is named–remains at the heart of many of the criticisms of Neyman-Pearson (N-P) statistics (and cognate methods). Yet as Birnbaum insisted, the “confidence concept” is the “one rock in a shifting scene” of statistical foundations, insofar as there’s interest in controlling the frequency of erroneous interpretations of data. (See my rejoinder.) Birnbaum bemoaned the lack of an explicit evidential interpretation of N-P methods. Maybe in 2017? Anyway, it’s 6 hrs later here, so I’m about to leave for that spot in the road… If I’m picked up, I’ll add an update at the end.**

You know how in that (not-so) recent Woody Allen movie, “Midnight in Paris,” the main character (I forget who plays it, I saw it on a plane) is a writer finishing a novel, and he steps into a cab that mysteriously picks him up at midnight and transports him back in time where he gets to run his work by such famous authors as Hemingway and Virginia Wolf? He is impressed when his work earns their approval and he comes back each night in the same mysterious cab…Well, imagine an error statistical philosopher is picked up in a mysterious taxi at midnight (New Year’s Eve ~~2011~~ ~~2012~~, ~~2013~~, ~~2014~~, ~~2015~~, 2016) and is taken back fifty years and, lo and behold, finds herself in the company of Allan Birnbaum.[i] There are a couple of brief (12/31/14 & 15) updates at the end.

ERROR STATISTICIAN: It’s wonderful to meet you Professor Birnbaum; I’ve always been extremely impressed with the important impact your work has had on philosophical foundations of statistics. I happen to be writing on your famous argument about the likelihood principle (LP). (whispers: I can’t believe this!)

BIRNBAUM: Ultimately you know I rejected the LP as failing to control the error probabilities needed for my Confidence concept. Continue reading

## Allan Birnbaum: Foundations of Probability and Statistics (27 May 1923 – 1 July 1976)

*Today is Allan Birnbaum’s birthday. In honor of his birthday this year, I’m posting the articles in the *Synthese* volume that was dedicated to his memory in 1977. The editors describe it as their way of “paying homage to Professor Birnbaum’s penetrating and stimulating work on the foundations of statistics”. I paste a few snippets from the articles by Giere and Birnbaum. If you’re interested in statistical foundations, and are unfamiliar with Birnbaum, here’s a chance to catch up.(Even if you are,you may be unaware of some of these key papers.)*

**HAPPY BIRTHDAY ALLAN!**

*Synthese* Volume 36, No. 1 Sept 1977: *Foundations of Probability and Statistics*, Part I

**Editorial Introduction:**

This special issue of

Syntheseon the foundations of probability and statistics is dedicated to the memory of Professor Allan Birnbaum. Professor Birnbaum’s essay ‘The Neyman-Pearson Theory as Decision Theory; and as Inference Theory; with a Criticism of the Lindley-Savage Argument for Bayesian Theory’ was received by the editors ofSynthesein October, 1975, and a decision was made to publish a special symposium consisting of this paper together with several invited comments and related papers. The sad news about Professor Birnbaum’s death reached us in the summer of 1976, but the editorial project could nevertheless be completed according to the original plan. By publishing this special issue we wish to pay homage to Professor Birnbaum’s penetrating and stimulating work on the foundations of statistics. We are grateful to Professor Ronald Giere who wrote an introductory essay on Professor Birnbaum’s concept of statistical evidence and who compiled a list of Professor Birnbaum’s publications.THE EDITORS

## Midnight With Birnbaum (Happy New Year)

**Just as in the past 4 years since I’ve been blogging, I revisit that spot in the road at 11p.m., just outside the Elbar Room, get into a strange-looking taxi, and head to “Midnight With Birnbaum”. (The pic on the left is the only blurry image I have of the club I’m taken to.) I wonder if the car will come for me this year, given that my Birnbaum article has been out since 2014… The (Strong) Likelihood Principle–whether or not it is named–remains at the heart of many of the criticisms of Neyman-Pearson (N-P) statistics (and cognate methods). Yet as Birnbaum insisted, the “confidence concept” is the “one rock in a shifting scene” of statistical foundations, insofar as there’s interest in controlling the frequency of erroneous interpretations of data. (See my rejoinder.) Birnbaum bemoaned the lack of an explicit evidential interpretation of N-P methods. Maybe in 2016? Anyway, it’s 6 hrs later here, so I’m about to leave for that spot in the road…**

You know how in that (not-so) recent Woody Allen movie, “Midnight in Paris,” the main character (I forget who plays it, I saw it on a plane) is a writer finishing a novel, and he steps into a cab that mysteriously picks him up at midnight and transports him back in time where he gets to run his work by such famous authors as Hemingway and Virginia Wolf? He is impressed when his work earns their approval and he comes back each night in the same mysterious cab…Well, imagine an error statistical philosopher is picked up in a mysterious taxi at midnight (New Year’s Eve ~~2011~~ ~~2012~~, ~~2013~~, ~~2014~~, 2015) and is taken back fifty years and, lo and behold, finds herself in the company of Allan Birnbaum.[i] There are a couple of brief (12/31/14 & 15) updates at the end.

ERROR STATISTICIAN: It’s wonderful to meet you Professor Birnbaum; I’ve always been extremely impressed with the important impact your work has had on philosophical foundations of statistics. I happen to be writing on your famous argument about the likelihood principle (LP). (whispers: I can’t believe this!)

BIRNBAUM: Ultimately you know I rejected the LP as failing to control the error probabilities needed for my Confidence concept.

ERROR STATISTICIAN: Yes, but I actually don’t think your argument shows that the LP follows from such frequentist concepts as sufficiency S and the weak conditionality principle WLP.[ii] Sorry,…I know it’s famous…

BIRNBAUM: Well, I shall happily invite you to take any case that violates the LP and allow me to demonstrate that the frequentist is led to inconsistency, provided she also wishes to adhere to the WLP and sufficiency (although less than S is needed).

ERROR STATISTICIAN: Well I happen to be a frequentist (error statistical) philosopher; I have recently (2006) found a hole in your proof,..er…well I hope we can discuss it.

BIRNBAUM: Well, well, well: I’ll bet you a bottle of Elba Grease champagne that I can demonstrate it! Continue reading

## Statistical “reforms” without philosophy are blind (v update)

Is it possible, today, to have a fair-minded engagement with debates over statistical foundations? I’m not sure, but I know it is becoming of pressing importance to try. Increasingly, people are getting serious about methodological reforms—some are quite welcome, others are quite radical. Too rarely do the reformers bring out the philosophical presuppositions of the criticisms and proposed improvements. Today’s (radical?) reform movements are typically launched from criticisms of statistical significance tests and P-values, so I focus on them. Regular readers know how often the P-value (that most unpopular girl in the class) has made her appearance on this blog. Here, I tried to quickly jot down some queries. (Look for later installments and links.) *What are some key questions we need to ask to tell what’s true about today’s criticisms of P-values? *

*I. To get at philosophical underpinnings, the single most import question is this:*

**(1) Do the debaters distinguish different views of the nature of statistical inference and the roles of probability in learning from data? ** Continue reading

## Joan Clarke, Turing, I.J. Good, and “that after-dinner comedy hour…”

I finally saw *The Imitation Game* about Alan Turing and code-breaking at Bletchley Park during WWII. This short clip of Joan Clarke, who was engaged to Turing, includes my late colleague I.J. Good at the end (he’s not second as the clip lists him). Good used to talk a great deal about Bletchley Park and his code-breaking feats while asleep there (see note[a]), but I never imagined Turing’s code-breaking machine (which, by the way, was called the Bombe and not Christopher as in the movie) was so clunky. The movie itself has two tiny scenes including Good. Below I reblog: “Who is Allowed to Cheat?”—one of the topics he and I debated over the years. Links to the full “Savage Forum” (1962) may be found at the end (creaky, but better than nothing.)

[a]”Some sensitive or important Enigma messages were enciphered twice, once in a special variation cipher and again in the normal cipher. …Good dreamed one night that the process had been reversed: normal cipher first, special cipher second. When he woke up he tried his theory on an unbroken message – and promptly broke it.” This, and further examples may be found in this obituary

[b] Pictures comparing the movie cast and the real people may be found here. Continue reading

## Midnight With Birnbaum (Happy New Year)

**Just as in the past 3 years since I’ve been blogging, I revisit that spot in the road at 11p.m.*,just outside the Elbar Room, get into a strange-looking taxi, and head to “Midnight With Birnbaum”. I wonder if they’ll come for me this year, given that my Birnbaum article is out… This is what the place I am taken to looks like. [It’s 6 hrs later here, so I’m about to leave…]**

You know how in that (not-so) recent movie, “Midnight in Paris,” the main character (I forget who plays it, I saw it on a plane) is a writer finishing a novel, and he steps into a cab that mysteriously picks him up at midnight and transports him back in time where he gets to run his work by such famous authors as Hemingway and Virginia Wolf? He is impressed when his work earns their approval and he comes back each night in the same mysterious cab…Well, imagine an error statistical philosopher is picked up in a mysterious taxi at midnight (New Year’s Eve ~~2011~~ ~~2012~~, ~~2013~~, 2014) and is taken back fifty years and, lo and behold, finds herself in the company of Allan Birnbaum.[i] There are a couple of brief (12/31/14) updates at the end.

ERROR STATISTICIAN: It’s wonderful to meet you Professor Birnbaum; I’ve always been extremely impressed with the important impact your work has had on philosophical foundations of statistics. I happen to be writing on your famous argument about the likelihood principle (LP). (whispers: I can’t believe this!)

BIRNBAUM: Ultimately you know I rejected the LP as failing to control the error probabilities needed for my Confidence concept.

ERROR STATISTICIAN: Yes, but I actually don’t think your argument shows that the LP follows from such frequentist concepts as sufficiency S and the weak conditionality principle WLP.[ii] Sorry,…I know it’s famous…

BIRNBAUM: Well, I shall happily invite you to take any case that violates the LP and allow me to demonstrate that the frequentist is led to inconsistency, provided she also wishes to adhere to the WLP and sufficiency (although less than S is needed).

ERROR STATISTICIAN: Well I happen to be a frequentist (error statistical) philosopher; I have recently (2006) found a hole in your proof,..er…well I hope we can discuss it.

BIRNBAUM: Well, well, well: I’ll bet you a bottle of Elba Grease champagne that I can demonstrate it! Continue reading

## Has Philosophical Superficiality Harmed Science?

I have been asked what I thought of some criticisms of the scientific relevance of philosophy of science, as discussed in the following snippet from a recent *Scientific American* blog. My title elicits the appropriate degree of ambiguity, I think.

Quantum Gravity Expert Says “Philosophical Superficiality” Has Harmed PhysicsBy John Horgan | August 21, 2014 | 14

“I interviewed Rovelli by phone in the early 1990s when I was writing a story for

Scientific Americanabout loop quantum gravity, a quantum-mechanical version of gravity proposed by Rovelli, Lee Smolin and Abhay Ashtekar[i]

Horgan: What’s your opinion of the recent philosophy-bashing by Stephen Hawking, Lawrence Krauss and Neil deGrasse Tyson?

Rovelli: Seriously: I think they are stupid in this. I have admiration for them in other things, but here they have gone really wrong. Look: Einstein, Heisenberg, Newton, Bohr…. and many many others of the greatest scientists of all times, much greater than the names you mention, of course, read philosophy, learned from philosophy, and could have never done the great science they did without the input they got from philosophy, as they claimed repeatedly. You see: the scientists that talk philosophy down are simply superficial: they have a philosophy (usually some ill-digested mixture of Popper and Kuhn) and think that this is the “true” philosophy, and do not realize that this has limitations.Here is an example: theoretical physics has not done great in the last decades. Why? Well, one of the reasons, I think, is that it got trapped in a wrong philosophy: the idea that you can make progress by guessing new theory and disregarding the qualitative content of previous theories. This is the physics of the “why not?” Why not studying this theory, or the other? Why not another dimension, another field, another universe? Science has never advanced in this manner in the past. Science does not advance by guessing. It advances by new data or by a deep investigation of the content and the apparent contradictions of previous empirically successful theories. Quite remarkably, the best piece of physics done by the three people you mention is Hawking’s black-hole radiation, which is exactly this. But most of current theoretical physics is not of this sort. Why? Largely because of the philosophical superficiality of the current bunch of scientists.”

I find it intriguing that Rovelli suggests that “Science does not advance by guessing. It advances by new data or by a deep investigation of the content and the apparent contradictions of previous empirically successful theories.” I think this is an interesting and subtle claim with which I agree. Continue reading

## 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.