Results 281 to 290 of about 967,632 (327)

Randomization and statistical inference

Communications in Statistics, 1975
An expository discussion is presented of the arguments concerning the role of randomization in statistical inference from the results of a randomized experiment. Then some comparisons of the power of the Fisher randomization test to the normal theory F-test for the case of an unpaired, two-group, randomized experiment are given..
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Statistical Inference for Proportions

American Journal of Roentgenology, 2005
This is the 16th in the series designed by the American College of Radiology (ACR), the Canadian Association of Radiologists, and the American Journal of Roentgenology. The series, which will ultimately comprise 22 articles, is designed to progressively educate radiologists in the methodologies of rigorous clinical research, from the most basic ...
Caroline Reinhold, Lawrence Joseph
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Acceptability and statistical inference

Biometrika, 1974
SUMMARY The likelihood principle is criticized and the acceptability principle is enunciated. Most acceptable estimates are defined and some techniques for their calculation are developed. In the one-parameter case the most acceptable estimator is, under some conditions, median unbiased. Conditions for the strong consistency and asymptotic normality of
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Multiple Statistical Inferences

2000
Clinical trials often compare the efficacy of several new treatments and often use many efficacy variables. Also, after overall testing for significant differences, additional questions about subgroups differences or about what variables do or do not contribute to the efficacy results.
Ton J. Cleophas, Toine F. Cleophas, Aeilko H. Zwinderman   +2 more
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Inferring statistical complexity

Physical Review Letters, 1989
Statistical mechanics is used to describe the observed information processing complexity of nonlinear dynamical systems. We introduce a measure of complexity distinct from and dual to the information theoretic entropies and dimensions. A technique is presented that directly reconstructs minimal equations of motion from the recursive structure of ...
James P. Crutchfield, Karl Young
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Statistical models and statistical inference

1981
In the previous chapter we have seen how a simple statistical model can be fitted to data by estimating the unknown parameters and then making checks with residuals. After we have done this, various questions can be answered in terms of the fitted model.
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Statistical Inference Techniques

2019
This chapter presents the most common and useful tests of hypothesis for bioinformatics applications. The hypothesis tests divide essentially into two categories: parametric and nonparametric. At the first category belong those tests based on the assumption of knowing the distribution of the sampling population(s) and inference is drawn on one or more ...
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Statistical Inference

2009
Often scientific information on various data generating processes are presented in the from of numerical and categorical data. Except for some very rare occasions, generally such data represent a small part of the population, or selected outcomes of any data generating process.
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Identification in statistical inference

Statistica Neerlandica, 1977
SummaryThe paper deals with the concept of identification in inferential statistics. At first a general concept of identification is defined and developed. Thereafter, the general theory is applied to univariate linear regression and simultaneous equation systems.
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On the Foundations of Statistical Inference

Journal of the American Statistical Association, 1962
Abstract The concept of conditional experimental frames of reference has a significance for the general theory of statistical inference which has been emphasized by R. A. Fisher, D. R. Cox, J. W. Tukey, and others. This concept is formulated as a principle of conditionality, from which some general consequences are deduced mathematically. These include
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