Of course, the rationale of PME is so different from what has been taught in “orthodox” statistics courses for fifty years, that it causes conceptual hangups for many with conventional training. But beginning students have no difficulty with it, for it is just a mathematical model of the natural, common sense way in which anybody does conduct his inferences in problems of everyday life.
The difficulties that seem so prominent in the literature today are, therefore, only transient phenomena that will disappear automatically in time. Indeed, this revolution in our attitude toward inference is already an accomplished fact among those concerned with a few specialized applications; with a little familarity in its use its advantages are apparent and it no longer seems strange. It is the idea that inference was once thought to be tied to frequencies in random experiments, that will seem strange to future generations.
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- Boltzmann, L.: 1877, Wiener Berichte 76, 373.Google Scholar
- Cox, R. T.: 1946, Am. Jour. Phys. 17, 1.Google Scholar
- Cox, R. T.: 1961, The Algebra of Probable Inference, Johns Hopkins University Press, Baltimore, Reviewed by E. T. Jaynes, Am. Jour. Phys. 31, 66, 1963.Google Scholar
- Cyranski, J.: 1979, Information and Control 33, 275–304.Google Scholar
- Darwin, G. C. and Fowler, R. H.: 1928, see account in R. H. Fowler (1936), Statistical Mechanics, Cambridge University Press.Google Scholar
- Eyring, H.: 1964, Statistical Mechanics and Dynamics, J. Wiley & Sons, Inc., New York.Google Scholar
- Gage, D. and Hestenes, D.: 1973, J. Stat. Phys. 7, 89.Google Scholar
- Gibbs, J. W.: 1902, Elementary Principles in Statistical Mechanics, reprinted (1961) by Dover Publishing Co., New York.Google Scholar
- Hobson, A.: 1972, J. Stat. Phys. 6, 189.Google Scholar
- Jaynes, E. T.: 1971, ‘The Well-Posed Problem’, in V. P. Godambe and D. A. Sprott, (eds.), Foundations of Statistical Inference, Holt, Rinehart & Winston of Canada, Toronto.Google Scholar
- Jaynes, E. T.: 1978, ‘Where Do We Stand on Maximum Entropy?’, in R. D. Levine and M. Tribus (eds.), The Maximum Entropy Formalism, M.I.T. Press, Cambridge MA.Google Scholar
- Jaynes, E. T.: 1980, “Marginalization and Prior Probabilities”, in A. Zellner (ed.), Bayesian Analysis in Econometrics and Statistics, North-Holland Publishing Co.Google Scholar
- Jaynes, E. T.: 1982, ‘On the Rationale of Maximum-Entropy Methods’, Proc. IEEE, 70, 939–952.Google Scholar
- Jeffreys, H.: 1939, 1948, Theory of Probability, Oxford University Press, 1st and 2nd editions.Google Scholar
- Savage, L. J.: 1954, The Foundations of Statistical Inference, J. Wiley & Sons, Inc., New York.Google Scholar
- Schrodinger, E.: 1948, Statistical Thermodynamics, Cambridge University Press.Google Scholar
- Tribus, M. and Motroni, H.: 1972, J. Stat. Phys. 4, 227.Google Scholar