tag:blogger.com,1999:blog-715339341803133734.post3930725932597740392..comments2017-07-19T13:11:05.567-05:00Comments on Maximum Entropy: ScientismTom Campbell-Rickettshttp://www.blogger.com/profile/07387943617652130729noreply@blogger.comBlogger3125tag:blogger.com,1999:blog-715339341803133734.post-26198832836234941232014-12-19T09:42:00.599-06:002014-12-19T09:42:00.599-06:00"As I see it, conceptual analysis does nothin..."As I see it, conceptual analysis does nothing more than specialize in eliminating ambiguity in the relationship between symbol and signified - something that is inherently part of science, anyway. Your examples of "things" and "reality" are trivial empirical questions, and the concept of truth is already given, once we have the hardware in place to constitute a decision-making entity."<br /><br />Reducing ambiguity is a huge part of conceptual analysis, and it is indeed a part of the scientific method - but it is the <i>non-empirical part</i>, the part that comes before (as well as after) the empirical investigations. And it has a name - "philosophy". :)<br /><br />I don't think our natural conceptions of things like "thing" or "truth" are necessarily clear enough, I do think philosophizing and coming up with non-ambigous (and useful!) definitions and recognizing our preconceptions can be productive. <br /><br />"Of course, we would like to be able to boast a non-circular foundation for everything, but I'm afraid this is just not a luxury we can aspire to. You say that reasoning under uncertainty is founded on axiomatic principles of reasoning under certainty - well yes, but but where do those axioms come from? They are either arbitrary (hardly a satisfactory solution to the circularity problem), or else they are derived from our capacity to reason probabilistically. "<br /><br />I don't think there is any way to justify our most basic rational intuitions; they're what we use to judge everything else. For myself, I am convinced by deductive arguments that Bayesianism is the right way (e.g. Cox's Theorem) rather than being convinced by probabilistic arguments that logic is true (I'm not sure if you can even state that consistently). <br /><br />"Do they have any familiarity with the normal distribution? "<br /><br />No, but they can gain familiarity...<br /><br />"When I get some time, I'll develop an example and post it on the blog - hopefully, before too far into the new year."<br /><br />I'm looking forward to it!יאיר רזקhttps://www.blogger.com/profile/15798134654972572485noreply@blogger.comtag:blogger.com,1999:blog-715339341803133734.post-13195708851224044522014-12-16T10:23:06.333-06:002014-12-16T10:23:06.333-06:00Hi Yair
Interesting comments.
As I see it, conc...Hi Yair<br /><br />Interesting comments. <br /><br />As I see it, conceptual analysis does nothing more than specialize in eliminating ambiguity in the relationship between symbol and signified - something that is inherently part of science, anyway. Your examples of "things" and "reality" are trivial empirical questions, and the concept of truth is already given, once we have the hardware in place to constitute a decision-making entity.<br /><br />Of course, we would like to be able to boast a non-circular foundation for everything, but I'm afraid this is just not a luxury we can aspire to. You say that reasoning under uncertainty is founded on axiomatic principles of reasoning under certainty - well yes, but but where do those axioms come from? They are either arbitrary (hardly a satisfactory solution to the circularity problem), or else they are derived from our capacity to reason probabilistically. <br /><br />__<br /><br />Regarding a linear regression example, I would start with a case that is assumed to pass through the origin, so that there is only one parameter to estimate - the calculation can then be done numerically using a spread sheet, or if you would like to be able to extend it more easily to higher dimensionality, using some simple code. <br /><br />Do they have any familiarity with the normal distribution? They will need to be able to appreciate that each x-y pair used to fit the line has itself an associated probability distribution.<br /><br />When I get some time, I'll develop an example and post it on the blog - hopefully, before too far into the new year.<br />Tom Campbell-Rickettshttps://www.blogger.com/profile/07387943617652130729noreply@blogger.comtag:blogger.com,1999:blog-715339341803133734.post-46142462772414107572014-12-16T02:00:35.590-06:002014-12-16T02:00:35.590-06:00I would argue in contrast that there is a prior ba...I would argue in contrast that there is a prior basis of rational reasoning, which is conceptual analysis (which includes logic, mathematics, understanding language, and so on). Only on this basis can the metaphysical and propositional model underlying your domains of knowledge can be defined; e.g. only once you understanding "things" to exist in "reality" and propositions as being "true" if they correspond to reality can you define (again, using language and logic - conceptual analysis) the question of whether some proposition is true (your (1)). <br /><br />Conceptual analysis is what (good) philosophy is all about, and does NOT fall under the scientific method but rather justifies it - it is because of our understanding of what "truth" or "belief" are, for example, and by the application of logic and mathematics, that we can justify the use of Bayes' Rule as the way to seek out truth. <br /><br />If our methods of thinking were justified scientifically, we would have circularity - our methods justifying our methods. What we have instead, I suggest, is foundationalism - our methods for reasoning under uncertainty are founded on our methods for thinking about certainty (which are themselves axiomatic).<br /><br />The upshot of all of this is that the charge of Scientism CAN be correctly derogative when people maintain that we should apply the Scientific Method to conceptual questions. You don't do mathematics by empirical induction, and you don't do an analysis of what "morally good" means by induction (although what people think about when the use the word is important, at the philosophical level the point is to explicate a clear meaning rather than to describe the confused and varied uses in ordinary use). <br /><br />In practice, however, the charge of Scientism is usually leveled at applications of the Scientific Method where it DOES belong, as in e.g. the science of morality (which IS a science, although like all sciences it is based on arbitrary/philosophical definitions of its subject matter), rather than where it doesn't belong (as in e.g. coming up with said definitions). <br /><br />Yair<br /><br />P.S. On an unrelated question - I'm teaching some Scientific Method to highschoolers. I taught them Bayes Rule, but I can't find a nice and SIMPLE (highschoolers!) Baysian analog of simple linear regression - coming up with the parameters of for a line formula and the uncertainty in them from a Bayesian perspective. Can you perhaps direct me in the right direction?<br /><br />Cheers,<br />Yairיאיר רזקhttps://www.blogger.com/profile/15798134654972572485noreply@blogger.com