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Lecture 7

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chris wiggins edited this page May 7, 2018 · 7 revisions

Readings 2018-02-26

secondary source:

sections 3.4 3.6 3.7 from "The Empire of Chance"

primary sources:

after this please do briefly read the primary sources:

Fisher, R. A. (1955), "Statistical Methods and Scientific Induction". Journal of The Royal Statistical Society (B) 17: 69-78.

Neyman, J. (1956), "Note on an Article by Sir Ronald Fisher," Journal of the Royal Statistical Society. Series B (Methodological), 18: 288-294.

Pearson, E. S. (1955), "Statistical Concepts in Their Relation to Reality," Journal of the Royal Statistical Society, B, 17: 204-207.

2017

readings

  • Inference Experts: ONLY 3.4 3.6 3.7 are required

  • Fisher, R. A. (1955), "Statistical Methods and Scientific Induction". Journal of The Royal Statistical Society (B) 17: 69-78.

  • Neyman, J. (1956), "Note on an Article by Sir Ronald Fisher," Journal of the Royal Statistical Society. Series B (Methodological), 18: 288-294.

  • Pearson, E. S. (1955), "Statistical Concepts in Their Relation to Reality," Journal of the Royal Statistical Society, B, 17: 204-207.

Discussion

Fisher

  • bitter rivalry with Neyman and Pearson
  • a scientist, not just a mathematician
    • claimed that Neyman and Pearson were mathematicians with insufficient real world experience
  • did not view failure to reject null hypothesis (type II error) as an error
    • basically doesn't view failure to reject null hypothesis as a final decision
  • agreed with Neyman and Pearson on one point: Bayesians were wrong

Neyman and Pearson

  • more mathematically rigorous: formalized hypothesis testing, type I & II errors, power of tests
  • notable result is Neyman-Pearson lemma, which identifies the most powerful test at a given significance level
  • rejected probabilistic interpretation of power of hypothesis tests. Hence the use of the term power

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