Fisher and regression
Aldrich, John (2005) Fisher and regression. Statistical Science, 20, (4), 401-417. (doi:10.1214/088342305000000331).
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In 1922 R.A. Fisher introduced the modern regression model, synthesizing the regression theory of Pearson and Yule and the least squares theory of Gauss. The innovation was based on Fisher’s realization that the distribution associated with the regression coefficient was unaffected by the distribution of X. Subsequently Fisher interpreted the fixed X assumption in terms of his notion of ancillarity. This paper considers these developments against the background of the development of statistical theory in the early twentieth century.
|Digital Object Identifier (DOI):||doi:10.1214/088342305000000331|
|Additional Information:||Full text available logged in to Webcat|
|Keywords:||fisher, karl pearson, bartlett, regression, theory of errors, correlation, ancillary statistic, history of statistics|
|Subjects:||H Social Sciences > HA Statistics|
|Divisions:||University Structure - Pre August 2011 > School of Social Sciences > Economics
|Date Deposited:||15 May 2006|
|Last Modified:||06 Aug 2015 02:31|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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