A Statistical Reanalysis of the Classical Rutherford's Experiment

Voinov, Vassilly; Воинов, Е В

doi:10.1080/03610910903355499

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Cited by 3 publications

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“…The models are so close to each other that one can hardly develop a test with much larger power. The situation cannot be improved by increasing the sample size, because the larger the sample the closer the Poisson model (especially for small values of a parameter) will be to the binomial distribution (Voinov & Voinov 2010).…”

Section: Discussionmentioning

confidence: 99%

Poisson Versus Binomial: Appointment of Judges to the U.S. Supreme Court

Voinov¹,

Воинов²,

Rakhimova

2010

Aus NZ J of Statistics

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The problem of discriminating between the Poisson and binomial models is discussed in the context of a detailed statistical analysis of the number of appointments of the U.S. Supreme Court justices from 1789 to 2004. Various new and existing tests are examined. The analysis shows that both simple Poisson and simple binomial models are equally appropriate for describing the data. No firm statistical evidence in favour of an exponential Poisson regression model was found. Two attendant results were obtained by simulation: firstly, that the likelihood ratio test is the most powerful of those considered when testing for the Poisson versus binomial and, secondly, that the classical variance test with an upper-tail critical region is biased.

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Section: Discussionmentioning

confidence: 99%