Frequentist probability and frequentist statistics

  title={Frequentist probability and frequentist statistics},
  author={Jerzy Neyman},
  • J. Neyman
  • Published 1 September 1977
  • Psychology
  • Synthese
journal especially given to foundations of probability and statistics. The other stimulus is multiple: letters from friends calling my attention to a dispute in journal articles, in letters to editors, and in books, about what is described as 'the Neyman-Pearson school' and particularly what is described as Neyman's 'radical' objectivism. While being grateful to my friends for their effort to keep me informed, I have to admit that, owing to a variety of present research preoccupations, I have… 

Neyman’s Statistical Philosophy

The ambitious claim that truly inductive reasoning could be based on his concept of likelihood appeared "to take its place as a measure of rational belief when the authors are reasoning from the sample to the population,” and proceeded to develop some of its properties.

A frequentist interpretation of probability for model-based inductive inference

A frequentist interpretation of probability in the context of model-based induction, anchored on the Strong Law of Large Numbers (SLLN) and justifiable on empirical grounds is proposed.

Alphabet Soup

Confusion over the reporting and interpretation of results of commonly employed classical statistical tests is recorded in a sample of 1,645 papers from 12 psychology journals for the period 1990

The statistical theories of Fisher and of Neyman and Pearson: A methodological perspective

Most of the debates around statistical testing suffer from a failure to identify clearly the features specific to the theories invented by Fisher and by Neyman and Pearson. These features are

Prior Information in Frequentist Research Designs and Social (Non-epistemic) Influences: The Case of Neyman’s Sampling Theory

We analyze the issue of using prior information in frequentist statistical inference by bringing out the sampling theory of Jerzy Neyman (a key figure in frequentist statistics), which has so far

Where Fisher, Neyman and Pearson went astray: On the logic (plus some history and philosophy) of Statistical Tests

  • U. Saint-Mont
  • Mathematics
    Advances in Social Sciences Research Journal
  • 2018
Every scientific endeavour consists of (at least) two components: A hypothesis on the one hand and data on the other. There is always a more or less abstract level - some theory, a set of concepts,

Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations

Misinterpretation and abuse of statistical tests, confidence intervals, and statistical power have been decried for decades, yet remain rampant. A key problem is that there are no interpretations of

Confusion Over Measures of Evidence (p's) Versus Errors (α's) in Classical Statistical Testing

Confusion surrounding the reporting and interpretation of results of classical statistical tests is widespread among applied researchers, most of whom erroneously believe that such tests are

P Values are not Error Probabilities

Confusion surrounding the reporting and interpretation of results of classical statistical tests is widespread among applied researchers. The confusion stems from the fact that most of these

On the Logic (plus some history and philosophy) of Statistical Tests and Scientific Investigation

This contribution is on elementary models connecting both levels that have been very popular in psychological research - statistical tests and an elegant contemporary treatment of the latter theory.



Statistical Methods for Research Workers

The aim of the author is to apply accurate tests to practical data by systematically attacking small sample problems on their merits, and no attempt is therefore made to prove rigorously the various propositions upon which the theory rests.


In an earlier paper* we have endeavoured to emphasise the importance of placing in a logical sequence the stages of reasoning adopted in the solution of certain statistical problems, which may be

The Design of Experiments

  • J. I
  • Economics
  • 1936
AbstractREADERS of “Statistical Methods for Research Workers” will welcome Prof. Fisher's new book, which is partly devoted to a development of the logical ideas underlying the earlier volume and

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These notes cover the basic definitions of discrete probability theory, and then present some results including Bayes' rule, inclusion-exclusion formula, Chebyshev's inequality, and the weak law of

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This book has done more than any other to popularize the use of modern statistical methods and maintains its place as the standard work on its subject for the ordinary scientific worker.

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The accuracy of an estimate of a normally distributed quantity is judged by reference to its variance, or rather, to an estimate of the variance based on the available sample. In 1908 “Student”

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Owing to the work of the International Statistical Institute,* and perhaps still more to personal achievements of Professor A.L. Bowley, the theory and the possibility of practical applications of

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The problem of testing statistical hypotheses is an old one. Its origins are usually connected with the name of Thomas Bayes, who gave the well-known theorem on the probabilities a posteriori of the

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We shall distinguish two aspects of the problems of estimation . (i) the practical and (ii) the theoretical. The practical aspect may be described as follows: (i a ) The statistician is concerned

An Introduction to Probability Theory and Its Applications

Thank you for reading an introduction to probability theory and its applications vol 2. As you may know, people have look numerous times for their favorite novels like this an introduction to