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Synthese

, Volume 36, Issue 1, pp 97–131 | Cite as

Frequentist probability and frequentist statistics

  • J. Neyman
Article

Keywords

Frequentist Statistic Frequentist Probability 
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References

  1. [1]
    de Finetti, B., Probability, Induction and Statistics, John Wiley & Sons, New York, 1972.Google Scholar
  2. [2]
    A Selection of Early Statistical Papers of J. Neyman, University of California Press, Berkeley, 1967.Google Scholar
  3. [3]
    Neyman, J., ‘The Emergence of Mathematical Statistics’, in On the History of Statistics and Probability (ed. by D. B. Owen), Marcel Dekker, New York, 1976.Google Scholar
  4. [4]
    Neyman, J., ‘On the Use of Maximum Likelihood Estimators’, Bulletin of the International Statistical Institute 38, Part 1 (1961), 193–200.Google Scholar
  5. [5]
    Feller, W., An Introduction to Probability Theory and Its Applications, Vol. 1, John Wiley & Sons, New York, 3rd ed., 1968.Google Scholar
  6. [6]
    Harris, T. E., The Theory of Branching Processes, Springer-Verlag, Berlin, 1963.Google Scholar
  7. [7]
    Karlin, S., A First Course in Stochastic Processes, Academic Press, New York, 3rd ed., 1969.Google Scholar
  8. [8]
    Kolmogorov, A. N., Grundbegriffe der Wahrscheinlichkeitsrechnung, Julius Springer, Berlin, 1933.Google Scholar
  9. [9]
    Doob, J. L., Stochastic Processes, John Wiley & Sons, New York, 1953.Google Scholar
  10. [10]
    Dynkin, E. B., Markov Processes, Springer-Verlag, Berlin, 1965.Google Scholar
  11. [11]
    Loève, M., Probability Theory, Van Nostrand, New York, 2nd ed., 1960.Google Scholar
  12. [12]
    von Mises, R., Wahrscheinlichkeit Statistik und Wahrheit, Julius Springer, Vienna, 1936. See also von Mises, R., Probability Statistics and Truth (trans. H. Geiringer), George Allen and Unwin Ltd., London, 1957.Google Scholar
  13. [13]
    Borel, E., Elements de la Théorie des Probabilités, Hermann, Paris, 3rd ed., 1924.Google Scholar
  14. [14]
    Borel, E., Le Hasard, Hermann, Paris, 1920.Google Scholar
  15. [15]
    Neyman, J. and Pearson, E. S., ‘On the Use and Interpretation of Certain Test Criteria for Purposes of Statistical Inference’, Biometrika 20-A, Part 1 (1928), 175–240. (See also [17] 1–66.)Google Scholar
  16. [16]
    Neyman, J. and Pearson, E. S., ‘On the Problem of the Most Efficient Tests of Statistical Hypotheses’, Philosophical Transactions of the Royal Society of London 231 (1933), 289–337. (See also [17] 140–185.)Google Scholar
  17. [17]
    Joint Statistical Papers of J. Neyman and E. S. Pearson, University of California Press, Berkeley, 1967.Google Scholar
  18. [18]
    Neyman, J., Lectures and Conferences on Mathematical Statistics and Probability, Graduate School of U.S. Department of Agriculture, Washington, 2nd ed., 1952.Google Scholar
  19. [19]
    Brownlee, K. A., Statistical Theory and Methodology in Science and Engineering, John Wiley & Sons, New York, 1960.Google Scholar
  20. [20]
    Lehmann, E. L., Testing Statistical Hypotheses, John Wiley & Sons, New York, 1959. Translated into Russian, Polish, and Japanese.Google Scholar
  21. [21]
    Schmetterer, L., Einfürung in die Mathematische Statistik, Springer-Verlag, Vienna, 1966.Google Scholar
  22. [22]
    Berger, A. and Wald, A., ‘On Distinct Hypotheses’, Annals of Math. Stat. 20 (1949), 104–109.Google Scholar
  23. [23]
    Neyman, J. and Pearson, E. S., ‘The Testing of Statistical Hypotheses in Relation of Probabilities A Priori’, Proc. Cambridge Philos. Soc. 29 (1933), 492–510.Google Scholar
  24. [24]
    Wald, A., Statistical Decision Functions, John Wiley & Co., New York, 1950.Google Scholar
  25. [25]
    Davies, R. B., ‘Beta-Optimal Test and an Application to the Summary Evaluation of Experiments’, J. of the Royal Statistical Society 31 (1969), 524–538.Google Scholar
  26. [26]
    Neyman, J., ‘Optimal Asymptotic Tests of Composite Statistical Hypotheses’, Probability and Statistics (The Harald Cramér Volume) (ed. by U. Grenander), Almquist and Wiksells, Uppsala, Sweden, 1959, pp. 213–234.Google Scholar
  27. [27]
    Traxler, R. H., ‘Snag in the History of Factorial Experiments’, in On The History of Statistics (ed. by D. B. Owen), Marcel Dekker, New York, 1976, pp. 281–295.Google Scholar
  28. [28]
    Fisher, R. A., Statistical Methods for Research Workers, Oliver and Boyd, Edinburgh, 5th ed., 1934.Google Scholar
  29. [29]
    Fisher, R. A., The Design of Experiments, Oliver and Boyd, Edinburgh, 1936.Google Scholar
  30. [30]
    Fisher, R. A. and Yates, F., Statistical Tables for Biological, Agricultural and Medical Research, Hafner, New York, 6th ed., 1963.Google Scholar
  31. [31]
    Cochran, W. G., ‘The Vital Role of Randomization in Experiments and Surveys’, in The Heritage of Copernicus (ed. by J. Neyman), Massachusetts Institute of Technology Press, Cambridge, Massachusetts, 1974, pp. 445–463.Google Scholar
  32. [32]
    Neyman, J., ‘Experimentation With Weather Control’, J. of the Royal Statistical Society 130 (1967), 285–326.Google Scholar
  33. [33]
    Neyman, J., Scott, E. L., and Smith, J. A., ‘Areal Spread of the Effect of Cloud Seeding at the Whitetop Experiment’, Science 163 (1969), 1445–1449.Google Scholar
  34. [34]
    Neyman, J., Lovasich, J. L., Scott, E. L. and Wells, M. A., ‘Hypothetical Explanations of the Negative Apparent Effects of Cloud Seeding in the Whitetop Experiment’, Proc. U.S. Nat. Acad. Sci. 68 (1971), 2643–2646.Google Scholar
  35. [35]
    Harville, D. A., ‘Experimental Randomization: Who Needs It?’, The American Statistician 29 (1975), 27–31.Google Scholar
  36. [36]
    Neyman, J., ‘On the Two Different Aspects of the Representative Method’, J. Royal Stat. Soc. 97 (1934), 558–625. (Spanish version of this paper appeared in Estadistica, J. Inter-American Stat. Inst. 17 (1959), 587–651.)Google Scholar
  37. [37]
    Hansen, M. H. and Madow, W. G., ‘Some Important Events in the Historical Development of Sample Surveys’, in On the History of Statistics and Probability (ed. by D. B. Owen), Marcel Dekker, New York, 1976, pp. 73–102.Google Scholar
  38. [38]
    Robbins, H., ‘An Empirical Bayes' Approach to Statistics’, in Proc. Third Berkeley Symp. Math. Stat. and Prob., Vol. 1, University of California Press, Berkeley, 1956, pp. 157–164.Google Scholar
  39. [39]
    Neyman, J., ‘Two Breakthroughs in the Theory of Statistical Decision Making’, Rev. of the Intern. Stat. Inst. 30 (1962), 11–27. (In Spanish in Estadistica Espanola 18 (1963), 5–28; in Russian in Matematika 2 (1965), 113–132; in Bulgarian in Phys. Math. Journ., Bulgarian Acad. Sci. 10 (1967), 94–110.)Google Scholar
  40. [40]
    Neyman, J., ‘Outline of a Theory of Statistical Estimation Based on the Classical Theory of Probability’, Philosophical Transactions of the Royal Society of London 236 (1937), 333–380.Google Scholar
  41. [41]
    Neyman, J., ‘L'estimation Statistique Traitée comme un Problème Classique de Probabilité’, Actualities Scientifiques et Industrielles 739 (1938), 25–57. (Russian version of this paper appeared in Uspehi Matematicheskih Nauk 10 (1944), 207–229.)Google Scholar
  42. [42]
    Neyman, J., ‘Foundation of the General Theory of Statistical Estimation’, Actualities Scientifiques et Industrielles 1146 (1951), 83–95.Google Scholar
  43. [43]
    Hotelling, H. and Working, H., ‘Applications of the Theory of Errors to the Interpretation of Trends’, J. American Statistical Association 24 (1929), 73–85.Google Scholar
  44. [44]
    Hotelling, H., ‘The Generalization of Student's Ratio’, Annals of Math. Stat. 2 (1931), 360–378.Google Scholar
  45. [45]
    Scheffé, H., ‘A Method for Judging All Contrasts in the Analysis of Variance’, Biometrika 40 (1953), 87–104.Google Scholar
  46. [46]
    Miller, R. G., Simultaneous Statistical Inference, McGraw-Hill, New York, 1966.Google Scholar
  47. [47]
    Pytkowski, W., The Dependence of Income of Small Farms Upon Their Area, Outlay and Capital Invested in Cows, Biblioteka Pulawska, Warsaw, 1932.Google Scholar
  48. [48]
    Neyman, J. and Scott, E. L., ‘Field Galaxies and Cluster Galaxies: Abundances of Morphological Types and Corresponding Luminosity Functions’, in Confrontation of Cosmological Theories with Observational Data (ed. by M. S. Longair), D. Reidel Publishing Co., Dordrecht, 1974, pp. 129–140.Google Scholar
  49. [49]
    Neyman, J. and Puri, P., ‘A Structural Model of Radiation Effects in Living Cells’, Proceedings U.S. Nat. Acad. Sci. 73 (1976), 3360–3363.Google Scholar

Copyright information

© D. Reidel Publishing Company 1977

Authors and Affiliations

  • J. Neyman
    • 1
  1. 1.Statistical LaboratoryUniversity of CaliforniaBerkeley

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