[PoSt] Philsophy of Statistics


Probably A Mammal
I think the way Noesti explains positivism borders on scientism. A prominent feature of positivism is merely that knowledge can only be obtained through science as the sole source of authentic information due to its ability to be positively verified. This begs a ton of questions about verification in science. Nonetheless, it was an important part of the social scientific development because it looked the very trite notion that "the natural sciences are successful and can positively verify their results through scientific method; social science can use scientific method to verify their results." Notice how this begs a huge questions about how scientific theories can be verified by the instance of any experiment, and it assumes a continuum between physical and social phenomena in a very big way. Extending this, but certainly within its own lineage, came the logical positivists that sought to stay away from the sort of ontological commitments that make positivism seem so much like scientism in the way Noesti expounded--i.e., that because the only authentic knowledge is scientific, science is the only source of reality. This implies that ontology is founded in epistemology, which it need not be. Logical positivists instead focus on logic as the foundation of scientific reasoning and inference. They accept the positivist epistemology, make no ontological commitments, but only seek to find logical foundations. The key in the logical positivist philosophy is not verification per se, but logical certainty in our assertions. In fact, this is a bolder claim than the positivists could make! It is widely accepted that Karl Popper did a good job dislodging PoS from this view by recognizing the importance of falsification. In particular, this led PoS to look at "what is science?" and try to find what merits are required for an activity to be considered "scientific." Positive verification can never lead one to justify their theory. It is entirely question begging or moot. Of course, the extreme of Popper's position is that we cannot make any verification, only falsification, and all that is necessary is falsification. Kuhn, Lakatos, Lauden, and Feyerabend, among others, critiqued this over the decades revealing that our view of what is "science" is quite diverse and how one goes from evidence to theory and back again is not as objective and rigorous as the logical positivists would have us believe: there is no inductive logic. These postpositivist critiques are not uniform because it's like trying to say atheism as an anti-doctrine of religion is an ideology. It isn't, it's just a rejection of one. Postmodern critiques, however, do have certain features that are important to notice as they are a result of specifically critiquing the positivist and early responses. They highlight that facts don't speak for themselves and they must be interpreted. This requires semantic assumptions about our ways in which we analyze information. Method does not happen in a vacuum. It comes from a semantic structure with a provided syntax that defines what is grammatically correct and what each piece of the vocabulary means. Not every fact, therefore, is objective, because it is biased by the default position one takes regarding the facts, the assumptions behind their models of the world and theory, what other information they have been exposed to, and the community of science at that time. Kuhn especially focused on the cultural aspects of science, and that has played out as a large part of the postmodernist critique, as many people who use it as a pejorative usually do so in the sense that they're implying you think "anything goes because it's whatever people collectively say is true." That's obviously a strawman and ignores the significance of the critique. But now that I've ran along this train of thought for this long, I'll leave you all to

I was actually talking more about how philosophy has actually been applied historically in the social sciences than the philosophy itself (which I am much less aware of). What positivism is in a purely intelectual sense is very different than what the term has meant in the social sciences - that is what academics in those areas meant when they spared over positivism. This may well be one of those concepts (like culture) that changed its nature fundamentally when it was grafted from one area (in this case philosophy) to method (in the social sciences).


Probably A Mammal
That is true noetsi. My friend has been more involved in the social sciences than I have (getting her master degrees in economics and political science--international relations, specifically). From reading some of her books and my own studies in the social science, at least in the textbook perspective, they do tend to make a point about positivism. Historically it did play a significant role in the way social scientists perceived their field. This is quite different from positivism in PoS as a study of philosophy. This is true of all PoS, though. The work Sober does in the philosophy of biology, for instance, doesn't necessarily reflect any great trends in actual biological work or the culture thereof. Similarly, the work of Cartwright hasn't particularly driven econometrics anywhere nor has any work of philosophers in physics driven the way we perceive ontological claims brought out by the latest works at CERN. These are all facets of actual scientific work performed by scientists. Though, to be fair, that line has blurred at times and especially by the training of the scientists and the extent of theoretical work they have done (e.g., Friedman and Keynes made considerable contributions to what we would now call the philosophy of economics while actually being working economists, but let us not forget economics is a very young field to which everybody making serious contributions were at the fore!).

I think this example should be considered significantly given that if we are discussing the philosophy of statistics, we have to be clear are we talking about it as a philosophy or merely speculating on the theorizing of practicing statisticians? They both have merits, and we're certainly all more involved with the latter, but the former is most aptly what I would think this thread is about.
Philosophy tends to be its own distinct world in academics. A central feature of positivism as applied to the social sciences after the second world war was to move away from philosophy to empirical analysis (which positivist in social science suggested was possible - that is basing answers purely on empirical investigation was possible and desirable). This is one of the things that gets hammered by post(anti) positivist of course and with good reason. It is impossible to conduct empirical research apart from theory and it would make little sense to do so.

Again I think it is critical to understand that positivism as applied to social sciences had much to do with politics, those who drove it believed that academics would have more respect and funding if it was perceived as a science (by which they meant an emphasis on empirical data and scientific method). And, in the context of the forties and fifties that was a reasonable view. I don't think that philosophy per se had much to do with this aside from a view like Herbert Simon and his impact had little to do with his logical positivism which few were aware of.

My guess is that most academic statisticians pay little attention to the underlying issues we are talking about. Because scientific method and empiricalism is so well accepted as to be invisible in their world (as in the hard sciences generally). It is only in areas like the social sciences where it was new and commonly not accepted that positivism became a major issue.
When I first saw this thread I thought that it would be about the difference in statistical “philosophy” between Fisher, Neyman-Pearsson and Baysians. So I looked at a paper by Lemann that you can find here .

The Lemann paper is interesting in itself but there was also mentioned a few books about “real” philosophy. I am just trying to read the latest one, but I can't really say if the book is good or bad. I don't know how much I understand either. Probably less then I think. Now, it is more true than ever that “all I know is that I know nothing” (quoted from a famous person).

I just want to share the refs for these books:

Seidenfeld, T. (1979) Philosophical problems of Statistical Inference, Boston

Kyburg H. E. Jr. (1974) The Logical Foundations of of Statistical Inference, Boston

Hacking, I. (1965) Logic of Statistical Inference, New York

Braithwaite, R. B. (1979) Scientific Explanation, Cambridge


Lemann, E. L. (1993) The Fisher, Neyman-Pearsson Theories of Testing Hypothesis: One Theory of Two, JASA


Dark Knight
Thanks Greta for the references.

I have recently read novel by author of Dilbert, God's debris (Reading the sequel now). Easy read and nice one (trinker may hate, Jake may like). Law of probability is the main theme of the novel. Not dealing with any statistical concepts except using the name "probability".


Dark Knight
After reading some PoS article, now I am able to follow this thread. Now I understand the jargon like epistemology, ontology, positivist, naturalist,realism, holism,.... It was very difficult to grasp in the beginning because nature of the topic. I realize that I need to unlearn some of the high school science. The debatable questions like "what is science ?" "pseudo science". "social science", and problems in categorizations were too confusing initially. Best part is reading again and again (same article) gave me lot of insights. Currently I am reading book by Rosenberg, Philosophy of social science

Now come back to statistics. There is a wiki page on philosophy of statistics we could also add philosophy of probability in our discussions. I found the references are useful (some of them were already mentioned in the previous posts). I have started reading the articles one by one. I will try to answer some of the smoothjohn's questions.

There is a philosophy forum in stackexchange. Philosophy of mathematics is discussed there. As of now I haven't seen PoSt related questions. I hope there would be many of such questions in the future.

I found some of the hacking lectures in youtube. Here is one and there are more.


Probably A Mammal
I don't know if I mentioned it before, but to me I think philosophy of statistics has a solid place in the epistemology studied in the various philosophy of sciences, because (1) statistics is used primarily in the various sciences, and (2) statistics is principally concerned with obtaining information ("knowledge"), usually through inference. That's simplistic, I know, but my point is that when exploring philosophy, be cognizant of things not about statistics directly, but which are still relevant. I've mentioned Elliot Sober's book before. It's basically a book about epistemology in the area of biology (philosophy of biology). The entire first chapter is about statistics, though. I've been reading a bit of philosophy of economics stuff, and I think it is also relevant since there is a lot of talk about causality (can economics achieve it?), and causality in statistics or inductive inference is an important topic. That raises another point, a lot of the time they don't even talk about statistics when they are talking about statistics. Usually they generalize to induction, inductive inference, or inductive logic when talking about the same thing, essentially. One thing I find interesting is the role statistics plays in theory development. By theory in philosophical terms, I mean "a collection of statements that explain a body of disparate phenomena." Moreover, we might append to this definition that theories are truth-seeking. By this I mean that we don't simply take those statements to be true or serve a pragmatic (see "predictive") purpose, but that those statements are true about the world (phenomena) that they explain. This is a point of consternation in economics because often the theory is making false statements, particularly when they're behavioral--e.g., people do not behave rationally in the way economics demands for their theory to be true about markets.

Anyway, I could lecture for days about philosophy of economics :D Thinking about it now, it's kind of disgusting how many books on it I've read (especially if I include PoS generally) lol

My current reading material: http://www.amazon.com/Preference-Choice-Welfare-Daniel-Hausman/dp/1107695120


Dark Knight
I have recently gone through some of the articles on genrel laws and causality. Until the "smoking debate" attitude of statistics was not used to establish causality. Fisher or statisticians in the beginning of 20th century considered "statistics is only about association". Last 3-4 decades, different causality establishing techniques developed in statistics. Rubin causal model, structural equation models, granger causality are few of them. counter-factual definition and/or time lag analysis are the key elements to establish the causality. It is not statistics alone is used to establish the causality. Statistics and the context mechanism (experience based and mechanistic) is used to establish the relationship.

I yet to read PoSt articles. Still spending time on PoS articles. Planning to read some articles related to my research (rationality; fall under philosophy of economics).

I found following paragraph (by FA Hayek) interesting.
How little statistics can contribute, however, even in such cases, to the explanation of complex phenomena is clearly seen if we imagine that computers were natural objects which found in sufficiently large numbers and whose behavior we wanted to predict. It is clear that we should never succeed in this unless we possessed the mathematical knowledge built into computers, that is, unless we knew the theory of determining their structure. No amount of statistical information on the correlation between input and output would get us any nearer our aim. Yet the efforts which are made on a large scale with regard to the much more complex structures which we call organisms are of the same kind. The belief that it must be possible in this manner to discover by observation regularities in the relations between input and output without the possession of an appropriate theory in this case appears even more futile and naive than it would be in the case of the computers.
It is from a 1978 article named "The theory of complex phenomena"


Probably A Mammal
I thought this would be an interesting read. While it is not directly about PoSt, it is about PoS and the relationship between philosophy and the sciences as practiced. This is an important issue, as I put on my philosopher hat, because I find great value in philosophy. However, I also can sympathize with the arguments that philosophy has fallen behind by not keeping up with the sciences. I think a small subset of naturalist philosophy is really the only route to keeping philosophy alive with respect the sciences. Otherwise, it's really nothing but an adjunct to the literary and historical disciplines. While that can be valuable, I find it's greatest merit in its relationship to application, particularly to the sciences. Now, I am a bit biased, since my focus in philosophy began with ethics and ended with the philosophy of science, particularly philosophy of mathematics, philosophy of economics, and rationality. All of these have been partly with respect to abstract thinking, but largely with regard the fact it's looking at the forest instead of the trees that comprise these scientific disciplines I'm passionate about. While the discourse on PoSt is light, the consequences to a divorce of philosophy and science apply just as focused on PoSt as other areas that could be lumped into the philosophy of science.




Probably A Mammal
Since I'm using this Feedly app on my phone to subscribe to the only RSS feed I read, I've been keeping up on some of the articles that get updated or added to the Stanford Encyclopedia of Philosophy (SEP). Today I read a very nice one that lays out a topic I'm very interested in that has direct application to PoSt. The author makes a point to distinguish this topic from issues in inductive logic. Instead, this requires an understanding of formal logic and probability theory, because the point of probability logic is to take classical (propositional) logic, at the very least, and include probability functions to track uncertainty (error) propagation. Very interesting, especially when you start looking at more complex logics that are available (modal, prepositional, relevant, and more).


If anybody can track down these articles from one of my top five favorite philosophers (he teaches just a few hours from me too v_v), I'd love to read them!

Van Fraassen, Bas. 1981. Probabilistic Semantics Objectified: I. Postulates and Logics. Journal of Philosophical Logic, 10: 371–391.
–––. 1983. Gentlemen's Wagers: Relevant Logic and Probability. Philosophical Studies, 43: 47–61.
–––. 1984. Belief and the Will. Journal of Philosophy, 81: 235–256.

If anybody is wondering who my other in the top 5 philosophers are, in no particular order: John Stuart Mills, Nancy Cartwright, Thomas Kuhn, and John Searle. I'd have to throw Amartya Sen in there, but I don't know if he's every been considered a philosopher, proper. He's an economist from that classical tradition that is highly theoretical and philosophical, which is why I love his work.
Until the "smoking debate" attitude of statistics was not used to establish causality.
They still aren't :p People decided instead that it was likely that smoking caused cancer based on the odds. Only in the last decade or so has it become clear (well somewhat clearer perhaps) what the physical process of smoking causing cancer. Which was tied to medical research/discovery not statistics. If you can't 1) create a theory to explain something and 2) show some of the basic mechanisms involved (at least in theory) you really don't have a basis to claim a causal link regardless of statistics.

Just ask Justice Scalia who just last year argued statistics can never be proof because there could always be an alternative cause :)


Probably A Mammal
I think the point is that people just didn't think of statistics as supporting causal claims. Their efficacy is another matter. But you cannot separate "medical research" from statistics considering the design of those experiments on many cases is a product of statistics! On a philosophical note, there is much in the way of how theoretical models can justify causal claims. The key here is that you can never prove them. You merely justify the claim. Theory itself just provides an explanation of how that causal relationship works. But it is entirely possible that this explanation is accurate in prediction but not how the mechanics actually work. Something else is required to make a theory (explanation) actually how the phenomena occurs.


Probably A Mammal
Since I am God-Master of PoST now, I figured I should share this gem I was told about last week. Along with the Stanford Encyclopedia of Philosophy (SEP), this is going to become one of my major sources of relevant research. It's focused on the philosophy of science and contains many pre-prints. For somebody like me that doesn't have access to JSTOR or some of the other closed-access aggregators, this is a valuable resource. If I find stuff on PoST, I'll definitely pass it along from there. I've subscribed to the RSS for 2013 so I'll always see the latest additions. I do the same with SEP to see new entries and revisions made.



Probably A Mammal
I guess this properly would go here: http://philsci-archive.pitt.edu/9774/1/nonprobchance.pdf

Abstract said:
"Chance" crops up all over philosophy, and in many other areas. It is often assumed -- without argument -- that chances are probabilities. I explore the extent to which this assumption is really sanctioned by what we understand by the concept of chance.
I'll say a few words once I find the time to read it. The abstract is utterly lacking in content, so it makes me question how good the content will actually be. Nevertheless, there's your PoSt reading for this week! ;)


Can't make spagetti
i know this may sound weird... but are there any VLOGS like youtube stuff preferably about this? i've started to realize that cardio sessions are great learning moments for me if i can just find the right podcast or video to listen to...


Probably A Mammal
Oh I know, that's how I've been getting my cardio all year. I bike at the gym watching Coursera lectures!

Personally, I prefer reading about philosophy. Often lectures don't do it justice and are better for discussions. I do enjoy when prominent philosophers give keynote speeches and such, but in the philosophy of science? Eh, that's not too common! I'll keep an eye open for any videos I come across, though.


Can't make spagetti
i caught this documentary like WAAAAAAAY a few years back on 4am re-runs and found it fascinating. then i saw that youtube has it as well.

does it look/sound interesting? you're right, ideally one should be able to read and reflect on what is being read... unfortunately (at least for me) real life says otherwise so i need to make-do with whatever i can...