R.A.FISHER: Statistical Methods and Scientific Inference

In honor of R.A. Fisher’s birthday this week (Feb 17), in a year that will mark 50 years since his death, we will post the “Triad” exchange between  Fisher, Pearson and Neyman, and other guest contributions*

by Sir Ronald Fisher (1955)

SUMMARY

The attempt to reinterpret the common tests of significance used in scientific research as though they constituted some kind of  acceptance procedure and led to “decisions” in Wald’s sense, originated in several misapprehensions and has led, apparently, to several more.

The three phrases examined here, with a view to elucidating they fallacies they embody, are:

  1. “Repeated sampling from the same population”,
  2. Errors of the “second kind”,
  3. “Inductive behavior”.

Mathematicians without personal contact with the Natural Sciences have often been misled by such phrases. The errors to which they lead are not only numerical.

TO CONTINUE READING R. A. FISHER’S  PAPER, CLICK HERE.

*If you wish to contribute something in connection to Fisher, send to error@vt.edu

Categories: Statistics | Tags: , , , , , , | 6 Comments

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6 thoughts on “R.A.FISHER: Statistical Methods and Scientific Inference

  1. Jean

    I think your tribute is spot-on for in the words of R. A. Fisher:

    “The History of Science has suffered greatly from the use by teachers of second-hand material, and the consequent obliteration of the circumstances and the intellectual atmosphere in which the great discoveries of the past were made. A first-hand study is always instructive, and often … full of surprises.”
    R.A. Fisher, 1955
    (p. 6, Experiments in plant hybridisation / G. Mendel. Edinburgh : Oliver & Boyd, 1965)
    http://www.adelaide.edu.au/library/special/digital/fisher/

    Seeing the original “Triad” (Fisher, Pearson, Neyman) posted on the blog was liking seeing an old friend! and reminded me of the fun we had at the PHORS reading groups when I was a graduate student at VT.

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  3. Hmm, well it would have been interesting to see what teaching Fisherian, and Neyman – Pearson statistics would have looked like, teaching from “first-hand” material. Had the latter methodology not been cleaned up in texts so as to appear within a decision-theoretical framework, I think, it would have been better. But, on the other hand, they could have objected, I suppose.

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