On a two-sample procedure for testing Student's hypothesis using mean range
Josef Machek (1959)
Aplikace matematiky
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Displaying similar documents to “Berry-Esseen type estimations for multi-sample -statistics.”
On a two-sample procedure for testing Student's hypothesis using mean range
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W. Klonecki (1964)
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On two theorems of Bartoszewicz
K. Sarkadi (1980)
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A non-parametric test of comparing dispersions
W. Sadowski (1960)
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Reform of studies in mathematical statistics, actuarial mathematics and econometrics in Czechoslovakia
(1948)
Aktuárské vědy
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Five Turning Points in the Historical Progress of Statistics - My Personal Vision
von Collani, Elart (2014)
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Statistics has penetrated almost all branches of science and all areas of human endeavor. At the same time, statistics is not only misunderstood, misused and abused to a frightening extent, but it is also often much disliked by students in colleges and universities. This lecture discusses/covers/addresses the historical development of statistics, aiming at identifying the most important turning points that led to the present state of statistics and at answering the questions “What went...
Applied statistics in designing special organic mixtures.
Eddy, Nnabuk O. (2007)
APPS. Applied Sciences
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Bootstrap method for central and intermediate order statistics under power normalization
Haroon Mohamed Barakat, E. M. Nigm, O. M. Khaled (2015)
Kybernetika
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It has been known for a long time that for bootstrapping the distribution of the extremes under the traditional linear normalization of a sample consistently, the bootstrap sample size needs to be of smaller order than the original sample size. In this paper, we show that the same is true if we use the bootstrap for estimating a central, or an intermediate quantile under power normalization. A simulation study illustrates and corroborates theoretical results.