Traditional Estimation Procedures
Elart von Collani and
Klaus Dräger
Additional contact information
Elart von Collani: University of Würzburg
Klaus Dräger: University of Würzburg
Chapter Chapter 3 in Binomial Distribution Handbook for Scientists and Engineers, 2001, pp 32-56 from Springer
Abstract:
Abstract Having defined the quantity of interest to be the probability p of a specified event E leads to the problem of measuring the actual value p of p. Traditionally, measurement of stochastical quantities is called estimation, which constitutes the core of statistical science. The most successful attempt to develop an estimation theory is due to Jerzy Neyman, who introduced the concept of confidence intervals with guaranteed reliability and thereby identified precision as the ultimate aim of an estimation method. Large parts of the traditional theory of estimation were developed and established by Jerzy Neyman. However, some of his proposals were not taken up by the statistical community. Therefore, a brief outline of Neyman’s approach is given here, particularly because the ideas and methodology developed in the next chapters are based essentially on Neyman’s results.
Date: 2001
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4612-0215-8_3
Ordering information: This item can be ordered from
http://www.springer.com/9781461202158
DOI: 10.1007/978-1-4612-0215-8_3
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().