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imperfecto del subjuntivo
The beginning arithmetic student is astounded to see what can be done with algebra. The algebra student is astounded to see what can be done with calculus. Thence on to differential equations, eigenvalues, and math that has seemingly miraculous properties compared to the vocabularies of the plateaus that preceded it. Similarly with statistics, Buddha is marveling that such things can be done, not because they can't but because his statistical thinking is still too concrete. He may understand the rote mechanics of how to set up a Z-test or a correlation coefficient given a table of data. But he can't demonstrate how to employ the vocabulary of statistics to model problems the way the scientists he's criticizing have done. He can't duplicate their process of going from the "story problem" of the experiment design to the abstract statistical model. He's attempting the equivalent of grading a calculus test using only the rules of elementary algebra, and saying "Hey, you can't do that! There's no rule in algebra that says you can do that!"
Spot on. There's also the typical behaviour of an unsuccessful student in a maths-related subject who thinks that if they doesn't come across a solution immediately they'll never reach it. They need to learn how not to rush a conclusion -or a complete lack of it- by coordinating different parts of their mental process, including creativity (bad students think hard sciences are devoid of creativity).
Our guest apologist works at that level. He loses his patience and quickly jumps to conclusions, not surprisingly along the lines of what he was looking for in the very beginning, that is, epistemological hedonism in its purest form. Those conclusions come in many flavours: there are appeals to nasty intentions on part of scientist; there are pieces of reasoning by analogy, including images, like the mix-up of the one-slit diffraction pattern for a multi-wavelength wide slit and the Gaussian bell-shaped curve; and there's the "we need a larger hammer" syndrome (after the man who wanted to place a bolt using a hammer and kept failing). I'm amused when he does the latter and uses Wikipedia to widen the scope of information he's using wrong, like he pontificating around the generalised hyperbolic distribution when he still doesn't get what is Student's for.
From what you described and my personal experience as an educator I gather """"Buddha"""" has followed those kind of courses where problems are dealt in a stereotyped way. That's one of the reasons I kept mentioning the Schaum series-like aspect in all these posts: typical problems, typical solutions, no association outside the safe and tiny "sandbox" where the problem is played.
It's ironic that I have taught students at the School of Architecture how to use the critical values of the t-distribution for any degree of freedom (they don't learn this term in this context) in order to get the characteristic strength of their concrete while they work like building site managers. I had to explain why the optimal practical quantity of test pieces is three (two degrees of freedom) for small buildings and all its eventualities. So, a student of Architecture at UNBA (not only my alma mater but five Nobel Prize winners', """"Buddha"""") learns in Math II (201-202) how to use a Z value of 1.645 or 1.96 for a 95% confidence (one and two queue tests), but later uses a t value of 2.92 (or sometimes 2.35 or 2.13) for their real life test, and the reasons for that.
It's incredible """"Buddha"""" can't manage so simple things, because, let's be honest, it's no accident """"Buddha"""" 's posts are devoid of numerical figures in inverse proportion to the way they are overpopulated with adjectives and names dropped. Both in Statistics, Physics and the scientific method in general, he never reached the level where the most basic theory evolves into the practicalities of life. He may have taken that step in some "computer related thing" but not in the fields he's uselessly debating here.
