Some Logic and History of Hypothesis Testing

The foundations of statistics are controversial, as foundations usually are. The main controversy is between so-called Bayesian methods, or rather neo-Bayesian, on the one hand and the non-Bayesian, or ‘orthodox’, or sampling-theory methods on the other.1 The most essential distinction between these two methods is that the use of Bayesian methods is based on the assumption that you should try to make your subjective or personal probabilities more objective, whereas anti-Bayesians act as if they wished to sweep their subjective probabilities under the carpet. (See, for example, Good (1976).) Most anti-Bayesians will agree, if asked, that they use judgment when they apply statistical methods, and that these judgments must make use of intensities of conviction,2 but that they would prefer not to introduce numerical intensities of conviction into their formal and documented reports. They regard it as politically desirable to give their reports an air of objectivity and they therefore usually suppress some of the background judgments in each of their applications of statistical methods, where these judgments would be regarded as of potential importance by the Bayesian. Nevertheless, the anti-Bayesian will often be saved by his own common sense, if he has any. To clarify what I have just asserted, I shall give some examples in the present article.

[1]  I. J. Good,et al.  Which Comes First, Probability or Statistics? , 1956 .

[2]  I. Good Saddle-point Methods for the Multinomial Distribution , 1957 .

[3]  T C Chalmers,et al.  The importance of beta, the type II error and sample size in the design and interpretation of the randomized control trial. Survey of 71 "negative" trials. , 1978, The New England journal of medicine.

[4]  Patrick Suppes,et al.  Logic, Methodology and Philosophy of Science , 1963 .

[5]  I. Good Corroboration, Explanation, Evolving Probability, Simplicity and a Sharpened Razor , 1968, The British Journal for the Philosophy of Science.

[6]  B. Efron Does an Observed Sequence of Numbers Follow a Simple Rule? (Another Look at Bode's Law): Rejoinder , 1971 .

[7]  L. J. Savage Elicitation of Personal Probabilities and Expectations , 1971 .

[8]  James J. Leach,et al.  Science, Decision and Value , 1973 .

[9]  Irving John Good,et al.  The Estimation of Probabilities: An Essay on Modern Bayesian Methods , 1965 .

[10]  M. Kendall,et al.  The advanced theory of statistics , 1945 .

[11]  I. J. Good,et al.  Information, Rewards, and Quasi-Utilities , 1972 .

[12]  E. S. Pearson,et al.  On the Problem of the Most Efficient Tests of Statistical Hypotheses , 1933 .

[13]  A. Rényi On Measures of Entropy and Information , 1961 .

[14]  Oscar Kempthorne,et al.  Probability, Statistics, and data analysis , 1973 .

[16]  A. Hendrickson,et al.  Elicitation of Subjective Probabilities by Sequential Choices , 1972 .

[17]  I. J. Good,et al.  Explicativity: a mathematical theory of explanation with statistical applications , 1981, Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences.

[18]  J. F. Crook,et al.  The Powers and Strengths of Tests for Multinomials and Contingency Tables , 1982 .

[19]  E. S. Pearson,et al.  On the Problem of the Most Efficient Tests of Statistical Hypotheses , 1933 .

[20]  Mark Bartlett,et al.  THE STATISTICAL SIGNIFICANCE OF ODD BITS OF INFORMATION , 1952 .

[21]  W. Weaver,et al.  Probability, rarity, interest, and surprise. , 1948, The Scientific monthly.

[22]  D. Lindley A STATISTICAL PARADOX , 1957 .

[23]  William Feller,et al.  An Introduction to Probability Theory and Its Applications , 1951 .

[24]  Bradley Efron,et al.  Does an Observed Sequence of Numbers Follow a Simple Rule? (Another Look at Bode's Law) , 1971 .

[25]  I. Good A Bayesian Significance Test for Multinomial Distributions , 1967 .

[26]  I. Good The Bayesian Influence, or How to Sweep Subjectivism under the Carpet , 1976 .

[27]  I. Good On the Application of Symmetric Dirichlet Distributions and their Mixtures to Contingency Tables , 1976 .

[28]  G. Brier VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITY , 1950 .

[29]  E. Lehmann Testing Statistical Hypotheses , 1960 .

[30]  Irving John Good,et al.  A Subjective Evaluation of Bode's Law and an ‘Objective’ Test for Approximate Numerical Rationality , 1969 .

[31]  Robert B. Ash,et al.  Information Theory , 2020, The SAGE International Encyclopedia of Mass Media and Society.

[32]  L. J. Savage,et al.  Probability and the weighing of evidence , 1951 .

[33]  J. F. Crook,et al.  The Bayes/Non-Bayes Compromise and the Multinomial Distribution , 1974 .

[34]  Ganapati P. Patil,et al.  On the Evaluation of the Negative Binomial Distribution with Examples , 1960 .

[35]  D. A. Sprott,et al.  On Tests of Significance , 1976 .

[36]  H. Jeffreys,et al.  Theory of probability , 1896 .

[37]  A. F. Smith,et al.  Bayesian Analysis in Econometrics and Statistics: Essays in Honour of Harold Jeffreys , 1982 .

[38]  I. Good Some history of the hierarchical Bayesian methodology , 1980 .

[39]  Irving John Good,et al.  The Surprise Index for the Multivariate Normal Distribution , 1956 .

[40]  I. Good Significance Tests in Parallel and in Series , 1958 .