Abstract
Hypothesis testing throughout the 19th century was sporadic and was (1) based on large sample approximations to the distributions of test statistics that were (2) chosen on intuitive grounds.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Anscombe, F.J. (1956). Discussion of David, F.N., and Johnson, N.L., Some tests of significance with ordered variables, J. Roy. Statist. Soc., 18, 24–27
Bailar, J.C, and Mosteller, F. (1986). Medical Uses of Statistics. NEJM Books, Walt-ham, Mass.
Berger, J.O. (1985). Statistical Decision Theory and Bayesian Analysis, 2nd ed., Springer-Verlag, New York.
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences, 2nd ed. Lawrence Erlbaum, Hillsdale, N.J.
Fisher, R.A. (1955). Statistical methods and scientific induction, J. Roy. Statist. Soc., 17, 69–78.
Fisher, R.A. (1973). Statistical Methods and Scientific Inference, 3rd ed. Hafner Press, New York.
Kraemer, H.C., and Thiemann, S. (1987). How Many Subjects’? Statistical Power Analysis in Research. Sage Publications, Newbury Park, Calif.
Lehmann, E.L. (1986). Testing Statistical Hypotheses, 2nd ed. Wiley, New York, (1991 Wadsworth & Brooks/Cole, Pacific Grove).
Neyman, J. (1957). “Inductive behavior” as a basic concept of philosophy of science, Rev. Int. Statist. Inst., 25, 7–22.
Neyman, J., and Pearson, E.S. (1928). On the use and interpretation of certain test criteria for purposes of statistical inference, Biometrika, 20A, 175–240, 263-295.
Neyman, J., and Pearson, E.S. (1933). On the problem of the most efficient tests of statistical hypotheses, Phil. Trans. R. Soc., Ser. A, 231, 289–337.
Pearson, E.S. (1939). William Sealy Gosset, 1876-1937, Biometrika, 30, 205–250.
Pearson, E.S. (1966). The Neyman-Pearson story: 1926-34, in Research Papers in Statistical: Festschrift for J. Neyman (David, F.N. Ed.). Wiley, New York.
Reid, C. (1982). Neyman—From Life. Springer-Verlag, New York.
Schweder, T. (1988). A significance version of the basic Neyman-Pearson theory for scientific hypothesis testing, Scand. J. Statist., 15, 225–242.
Student (1908). On the probable error of a mean, Biometrika, 6, 151–164.
Wijsman, R.A. (1979). Constructing all smallest simultaneous confidence sets in a given class, with applications to MANOVA, Ann. Statist., 7, 1003–1018.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1992 Springer Science+Business Media New York
About this chapter
Cite this chapter
Lehmann, E.L. (1992). Introduction to Neyman and Pearson (1933) On the Problem of the Most Efficient Tests of Statistical Hypotheses. In: Kotz, S., Johnson, N.L. (eds) Breakthroughs in Statistics. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-0919-5_5
Download citation
DOI: https://doi.org/10.1007/978-1-4612-0919-5_5
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-94037-3
Online ISBN: 978-1-4612-0919-5
eBook Packages: Springer Book Archive