Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-23T15:31:01.306Z Has data issue: false hasContentIssue false

Theory of Statistical Estimation

Published online by Cambridge University Press:  24 October 2008

R. A. Fisher
Affiliation:
Gonville and Caius College.

Extract

It has been pointed out to me that some of the statistical ideas employed in the following investigation have never received a strictly logical definition and analysis. The idea of a frequency curve, for example, evidently implies an infinite hypothetical population distributed in a definite manner; but equally evidently the idea of an infinite hypothetical population requires a more precise logical specification than is contained in that phrase. The same may be said of the intimately connected idea of random sampling. These ideas have grown up in the minds of practical statisticians and lie at the basis especially of recent work; there can be no question of their pragmatic value. It was no part of my original intention to deal with the logical bases of these ideas, but some comments which Dr Burnside has kindly made have convinced me that it may be desirable to set out for criticism the manner in which I believe the logical foundations of these ideas may be established.

Type
Research Article
Copyright
Copyright © Cambridge Philosophical Society 1925

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

(1)Fisher, R. A. (1921). “The mathematical foundations of theoretical statistics.” Phil. Trans. A., vol. 222, pp. 309368.Google Scholar
(2)Fisher, R. A. (1920). “A mathematical examination of the methods of determining the accuracy of an observation by the mean error and by the mean square error.’ Monthly Notices of R.A.S. vol. 80, pp. 758770.CrossRefGoogle Scholar
(3)Fisher, R. A. (1924). “The conditions under which Χ2 measures the discrepancy between observation and hypothesis.” J.R.S.S. vol. 87, pp. 442450.Google Scholar