UMaine SMS 691 - Scientific Methods- Which one should I use

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Scientific Methods: Which one should I use?1Credits•Eugene Gallagher (UMass Boston) !•Lakatos, I. 1970. Falsification and the methodology of research programmes. pp. 91-196 in I. Lakatos and A. Musgrave, Eds. Criticism and the Growth of Knowledge. Cambridge Univ. Press. 2Outline•Introduction to identifying truth •Metaphors about the scientific process •Flawed approaches •Viable approaches3Perspectives•I am not now nor have I ever been an “authority” on how to do science. •My intent is to get you and your advisors into discussions of the operational procedures being used in your labs and that will be used during your careers. •Nothing would seem a higher priority in treating professional skills.4My experience in grad school•Lots of attention to statistical hypothesis testing (highly recommended) •Lots of attention to experimental and sampling design (highly recommended) •A little Popper •I.e., not very broad or deep exposure to the philosophy of science5•Consensus •Consistency •Authority •Revelation •Durability •ScienceFiltering truth•Consensus •Consistency •Authority •Revelation •Durability •Science18 September 2006 issue of The New Yorker•Consensus •Consistency •Authority •Revelation •Durability •ScienceElizabeth Wagele political cartoon <http://www.flickr.com/photos/12130602@N07/1377004814/>•Consensus •Consistency •Authority •Revelation •Durability •Science•Consensus •Consistency •Authority •Revelation •Durability •Science•Consensus •Consistency •Authority •Revelation •Durability •Science•Consensus •Consistency •Authority •Revelation •Durability •ScienceDouble-filtered truth?6Useful Metaphors•Products of science (what comes out of the factory): knowledge (data and theory, including textbooks) and technology !•Process of science (what is done in the factory): figuring out the rules by which nature works7~ Feynman“The first principle is that you must not fool yourself—and you are the easiest person to fool. So you have to be very careful about that. After you've not fooled yourself, it's easy not to fool other scientists. You just have to be honest in a conventional way after that.”http://calteches.library.caltech.edu/51/2/CargoCult.pdf“Philosophy of science is about as useful to scientists as ornithology is to birds.”What gets emphasized but may not be the most useful•The structure of scientific revolutions (Kuhn) — inspiring reading, but what should you do when the revolution is not raging? !•Deductive logic (Popper) — pretty useful, but very silent about where hypotheses come from and a little inaccurate; science is not a two-cornered fight between data and hypothesis; hypotheses are not discarded until a better one comes along9A brief tour of the Mausoleum“Isms” that should be dead, but aren’t quite10Don’t adopt one by accident or default.Essentialism•Credited to Aristotle !•Science is finding the true value or essence of a thing !•Not too bad an idea for, e.g., the “true” speed of light in a vacuum But a lousy idea for things biological or statistical mechanical11Classical Justificiationism•Build on a solid foundation !•Use only proven propositionsBut nothing can be proven in science (vs. mathematics).12Empiricism•“Just the facts Ma’am.” !•Theory may be fallible, so just stick with observations — hard data.But there is no clear boundary between theory and observation (e.g., to trust telescope obser- vations you need theory).13Probabilism•A.k.a. neoclassical justificationism !•So if evidence may be fallible, let’s weigh the quantities pro and con.Very easy to inject bias; never know when a road is becoming a dead end14Dogmatic Falsificationism•“The theoretician proposes, the experimenter — in the name of Nature — disposes.” ~Popper !•Emphasizes scientific honesty !•Admits impossibility of proofNo clear boundary between theory and observation; no disproof is possible, either.15Viable Ideas“Isms” that bear closer inspection and adoption16Strongly influenced by: Lakatos, I. 1970. Falsification and the methodology of research programmes. pp. 91-196 in I. Lakatos and A. Musgrave, Eds. Criticism and the Growth of Knowledge. Cambridge Univ. Press.This reference is available in Fogler and also can be read on Amazon.com.“Naïve” Methodological Falsificationism•Impossibility of proof and disproof admitted !•Asymmetry of hypothesis testing recognized !•Championed by Popper ~ “The belief that science proceeds from observation to theory is so widely and so firmly held that my denial of it is often met with incredulity ... But in fact the belief that we can start with pure observation alone, without anything in the nature of a theory, is absurd; as may be illustrated by the story of the man who dedicated his life to natural science, wrote down everything he could observe, and bequeathed his priceless observations to the Royal Society to be used as inductive evidence. This story should show us that though beetles may profitably be collected, observations may not.”17“Sophisticated” Methodological Falsification•But where is the creative side of science; where do hypotheses come from? !•Crucial experiments are a myth. !•Theories don’t die unless a replacement is in hand. That’s why theoreticians get more credit than they might appear to deserve. !•Emphasizes dramatic, unexpected, stunning predictions (Lakatos’ empirical conclusion) !•Important criticism is constructive.18Terms and ConditionsA mix of etymology and useful definitions19Proof•None in science — accepted ≠ proved !•Lawyer’s proof — convincing to 12/12 people vs. mathematician’s proof (in formalism within mathematics propositions can be proven given the verity of starting axioms; but not all math can be proven even in this sense. !•Scientific explanations are tentative — good until a better explanation comes along. (Newtonian mechanics lasted a long time before relativity came along.) !•Science gets a bum rap when we fail to explain this distinction. Science and Nature are good examples of lazy usage. Some fields are worse offenders than others.20Creative mathematicians seek ambiguity.Good statistical null hypotheses may be good or bad scientific hypotheses.Criteria for good hypotheses•Are connected, i.e., derive from a good thesis


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