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Testing Statistical Testing

  • Deborah Mayo
Chapter
Part of the The University of Western Ontario Series in Philosophy of Science book series (WONS, volume 16)

Abstract

At a recent conference on problems in economics the following problem was raised:

Econometricians like to think of themselves as scientists, and their methods as scientific. Students of the philosophy of science, on the other hand, have not had any notable success in relating the formal concepts of scientific method or the logic of scientific explanation and theory construction to either the method or the theory of econometrics [3, p. 238].

This should not be taken to mean that the theory and practice of economics and econometrics is not scientific. It rather points to the need for a greater effort among philosophers to tie their analyses to actual scientific practice. More specifically, it indicates a need for philosophers of science to examine statistical theorizing in science, since inference and explanation in economics is often statistical in nature.

Keywords

Bayesian Inference Sample Space Standard Methodology Bayesian Theory Likelihood Principle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    Barnard, G. A., ‘The logic of statistical inference’, British Journal of the Philosophy of Science 23 (1972), 123–190.CrossRefGoogle Scholar
  2. [2]
    Carnap, R., Logical Foundations of Probability, 2nd edition, University of Chicago Press, Chicago, 1962.Google Scholar
  3. [3]
    Cunnyngham, J., ‘Econometric model construction and predictive testing’, in Problems and Issues in Current Econometric Practice. Ed. K. Brunner, The Ohio State University, Ohio, 1972, pp. 238–261.Google Scholar
  4. [4]
    Edwards, A. W. F., Likelihood, Cambridge University Press, Cambridge, 1972.Google Scholar
  5. [5]
    Fisher, R. A., Statistical Methods and Scientific Inference, 2nd edition, Oliver and Boyd, Edinburgh, 1959.Google Scholar
  6. [6]
    Giere, R. N., ‘Bayesian statistics and biased procedures’, Synthese 20 (1969), 371–387.CrossRefGoogle Scholar
  7. [7]
    Godambe, V. P., and Sprott, D. A. (eds.), Foundations of Statistical Inference, Holt, Rinehart and Winston of Canada, Toronto, 1971.Google Scholar
  8. [8]
    Good, I. J., ‘Probability or Support?’, Nature 213 (1967), No. 5073, 233–234.Google Scholar
  9. [9]
    Good, I. J., ‘The Bayesian influence, or how to sweep subjectivism under the carpet’, in [12] Harper, W. L., and Hooker, C. A. (eds.), Foundations of Probability Theory, Statistical Inference, and Statistical Theories of Science, Vol. II, D. Reidel Publishing Co., Holland, 1976, pp. 125–174.Google Scholar
  10. [10]
    Goodman, N., Fact, Fiction, and Forecast, The Bobbs Merrill Company, Inc., New York, 1965.Google Scholar
  11. [11]
    Hacking, I., Logic of Statistical Inference, Cambridge University Press, Cambridge, 1965.Google Scholar
  12. [12]
    Harper, W. L., and Hooker, C. A. (eds.), Foundations of Probability Theory, Statistical Inference, and Statistical Theories of Science, Vol. II, D. Reidel Publishing Co., Holland, 1976.Google Scholar
  13. [13]
    Jaynes, E. T., ‘Confidence intervals vs Bayesian intervals’, in [12] Harper, W. L., and Hooker, C. A. (eds.), Foundations of Probability Theory, Statistical Inference, and Statistical Theories of Science, Vol. II, D. Reidel Publishing Co., Holland, 1976, pp. 175–213.Google Scholar
  14. [14]
    Lieberman, Bernhardt (ed.), Contemporary Problems in Statistics, Oxford University Press, New York, 1971.Google Scholar
  15. [15]
    Lindley, D. V., The estimation of many parameters’, in [7] Godambe, V. P., and Sprott, D. A. (eds.), Foundations of Statistical Inference, Holt, Rinehart and Winston of Canada, Toronto, 1971, pp. 435–447.Google Scholar
  16. [16]
    Lindley, D. V., ‘Bayesian statistics’, in [12] Harper, W. L., and Hooker, C. A. (eds.), Foundations of Probability Theory, Statistical Inference, and Statistical Theories of Science, Vol. II, D. Reidel Publishing Co., Holland, 1976, pp. 353–362.Google Scholar
  17. [17]
    Mayo, D., Philosophy of Statistics, Doctoral dissertation, University of Pennsylvania, 1979.Google Scholar
  18. [18]
    Mood, A. M., Graybill, F. A., and Boes, D. C., Introduction to the Theory of Statistics, 3rd edition, McGraw-Hill, Inc., New York, 1963.Google Scholar
  19. [19]
    Morrison, D. E. and Henkel, R. E. (eds.), The Significance Test Controversy — A Reader, Aldine Publishing Company, Chicago, 1970.Google Scholar
  20. [20]
    Neyman, J., First Course in Probability and Statistics, Henry Holt, New York, 1950.Google Scholar
  21. [21]
    Neyman, J. and Pearson, E. S., ‘On the problem of the most efficient tests of statistical hypotheses’, Philosophical Transactions of the Royal Society A231 (1933), 289–337.CrossRefGoogle Scholar
  22. [22]
    Rosenkrantz, R., ‘The significance test controversy’, Synthese 26 (1973), 304–321.CrossRefGoogle Scholar
  23. [23]
    Savage, L. J., The Foundations of Statistics, Wiley and Sons, Inc., New York, 1954.Google Scholar

Copyright information

© D. Reidel Publishing Company 1981

Authors and Affiliations

  • Deborah Mayo

There are no affiliations available

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