Abstract
The problem of testing statistical hypotheses is an old one. Its origins are usually connected with the name of Thomas Bayes, who gave the well-known theorem on the probabilities a posteriori of the possible “causes” of a given event.* Since then it has been discussed by many writers of whom we shall here mention two only, Bertrand† and Borel,‡ whose differing views serve well to illustrate the point from which we shall approach the subject.
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.
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
Neyman, J., Pearson, E.S. (1992). 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_6
Download citation
DOI: https://doi.org/10.1007/978-1-4612-0919-5_6
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