Planning and Executing Credible Experiments. Robert J. Moffat

Planning and Executing Credible Experiments - Robert J. Moffat


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view of an experiment is illustrated in Figure 1.1, which also shows some of the necessary features of the system design.

      Perhaps the most important feature of this view of experimental work is the important role given to uncertainty analysis. There are uncertainties in every measurement and, therefore, in every parameter calculated using experimental data. When the results of an experiment scatter (i.e. are different on repeated trials), the question always arises, “Is this scatter due to the uncertainties in the input data or is something changing in the experiment?”

      The last point we wish to make before sending you off into this body of work has to do with the level of expertise one needs to run good experiments.

      We think it is more important for an experimentalist to have a working knowledge of many areas than to be a specialist in any one. The lab is a real place; Mother Nature never forgets to apply her own laws. If you are unaware of the Coanda effect, you will wonder why the water runs under the counter instead of falling off the edge. If you haven't heard of Joule–Thomson cooling, you will have a tough time figuring out why you get frost on the valve of a CO2 system.

      Accordingly, if you aren't aware of the limitations of statistics, then using a statistical software package may lead you to indefensible conclusions.

      It is not necessary to be the world's top authority on any of the mechanisms you encounter in the lab. You simply have to know enough to spot anomalies, to recognize that something unexpected or interesting is happening, and to know where to go for detailed help.

      The lab is a great place for an observant generalist. The things that happen in the lab are real and reflect real phenomena. When something unexpected happens in the lab, if you are alert, you may learn something! As Pasteur said, “Chance favors only the prepared mind” (Pasteur 1854).

      Let’s now launch toward planning and executing credible experiments.

Schematic illustration of the Bundt cake as delivered. A high heat-transfer coefficient lifts the fluid batter like a hot air balloon.

      One night, years ago, my wife baked a Bundt cake (chocolate and vanilla batter layered in a toroidal pan). When she presented me with a slice of that cake for dessert, I was impressed. But, also, I noticed something interesting about the pattern the batter had made as it cooked.

      I recognized that the flow pattern, as drawn in figure 1.2, was related to the heat‐transfer coefficient distribution around the baking pan.

      I tried to impress my wife with my knowledge of heat transfer by explaining to her what I thought I saw. “Look,” I said, “see how the batter rose up in the center, and came down on the sides. That means that the batter got hot in the center sooner than it did on the edges. That means that the heat‐transfer coefficient is highest at the bottom center stagnation point for a cylinder in free convection with a negative Grashof number.”

      My wife was silent for a minute, then gently corrected me “I baked the cake upside down.”

      Of course, as soon as I learned that, I was able to say with confidence that “The heat‐transfer coefficient is lowest at the bottom center stagnation point and high on the sides, for a cylinder in free convection with a negative Grashof number.”

      The Moral of This Story?

      It is critically important that you can trust your data before you try to interpret it. Beware! Once we accept our results as valid, how can we avoid constructing or searching for an explanation? Does not the scientific method and our human nature spur us to do so?

      1 Carey, B. (2011). Fraud case seen as a red flag for psychology research. http://www.nytimes.com/2011/11/03/health/research/noted‐dutch‐psychologist‐stapel‐accused‐of‐research‐fraud.html.

      2 Ioannidis, J.P.A. (13 July 2005). Contradicted and initially stronger effects in highly cited clinical research. JAMA 294 (2): 218–228. https://doi.org/10.1001/jama.294.2.218. PMID 16014596.

      3 Pasteur L. (Dec. 7, 1854). “Dans les champs de l'observation le hasard ne favorise que les esprits préparés,” translated as “In the fields of observation chance favours only the prepared mind.” Lecture, University of Lille. http://en.wikiquote.org/wiki/Louis_Pasteur.

      1 1.1 Following the guide in Appendix D, Section D.1, download and install the statistical language R, which is open source and free. Please consider this software tool essential.

      2 Following the guide in Appendix D, Section D.2, download and install LibreOffice, open source and free.1.2 LibreOffice is compatible with msOffice documents. LibreOffice can even read and write antiquated *.doc and *.xls files of obsolete versions of msOffice better than ms does. The interface is more accessible and less bloated than msOffice. Consider this optional, but highly recommended and free.

      3 1.3 Following the guide in Appendix D, Section D.4, consider R‐Studio. Please consider this software tool optional.

      Notes

      1 1 Variations of the quote are attributed to Albert Einstein and to William Ian Beardmore Beveridge. In The Art of Scientific Investigation (1950), p. 65, “A theory is something nobody believes, except the person who made it. An experiment is something everybody believes, except


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