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The Effect of the Outliers and Leverage Points in the Construction of the Bayesian and Bootstrap Confidence Intervals [PDF]

المجلة العراقية للعلوم الاحصائية, 2019
The aim of this research is to compare the bootstrap confidence intervals with the Bayesian confidence intervals for smoothing splines as well as the traditional confidence intervals to determine which of these limits are best in the presence of Outliers
Muzahim Mohammed
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Confidence intervals and other statistical intervals in metrology [PDF]

International Journal of Metrology and Quality Engineering, 2012
Typically, a measurement is regarded as being incomplete without a statement of uncertainty being provided with the result. Usually, the corresponding interval of measurement uncertainty will be an evaluated confidence interval, assuming that the ...
Willink R.
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Confidence Intervals for Variance Components [PDF]

The Egyptian Statistical Journal, 1982
In the previous paper Estimation of Variance Components in the One-Way Random Effects Model (ESJ Vol. 25, No. 2, pp. 1-11), several methods for constructing confidence inte-rvals for the components of variance were presented. In the present paper we will
Oskar Feichtinger, Keh-Ming Husueh
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Confidence intervals for fMRI activation maps. [PDF]

PLoS ONE, 2013
Neuroimaging activation maps typically color voxels to indicate whether the blood oxygen level-dependent (BOLD) signals measured among two or more experimental conditions differ significantly at that location.
Stephen A Engel, Philip C Burton
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Confidence Intervals of COVID-19 Vaccine Efficacy Rates

Numeracy, 2021
This tutorial uses publicly available data from drug makers and the Food and Drug Administration to guide learners to estimate the confidence intervals of COVID-19 vaccine efficacy rates with a Bayesian framework.
Frank Wang
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Generalized Confidence Intervals for Zero-Inflated Pareto Distribution

Mathematics, 2021
This paper considers interval estimations for the mean of Pareto distribution with excess zeros. Three approaches for interval estimation are proposed based on fiducial generalized pivotal quantities (FGPQs), respectively.
Xiao Wang, Xinmin Li
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L'établissement d'une norme de qualification sûre dans un contexte non paramétrique [PDF]

Tutorials in Quantitative Methods for Psychology, 2008
La sélection de personnel pour un emploi se base souvent sur une norme psychométrique qu’un candidat doit atteindre afin d’être recruté. Or, cette norme est statistique, c’est-à-dire calculée sur les mesures d’un simple échantillon de la population ...
Louis Laurencelle
doaj  

Interval-Valued Intuitionistic Fuzzy Confidence Intervals

Journal of Intelligent Systems, 2019
Confidence intervals are useful tools for statistical decision-making purposes. In case of incomplete and vague data, fuzzy confidence intervals can be used for decision making under uncertainty.
Kahraman Cengiz, Oztaysi Basar, Cevik Onar Sezi   +2 more
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Confidence Intervals from Normalized Data: A correction to Cousineau (2005) [PDF]

Tutorials in Quantitative Methods for Psychology, 2008
Presenting confidence intervals around means is a common method of expressing uncertainty in data. Loftus and Masson (1994) describe confidence intervals for means in within-subjects designs. These confidence intervals are based on the ANOVA mean squared
Richard D. Morey
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Generating confidence intervals on biological networks

BMC Bioinformatics, 2007
Background In the analysis of networks we frequently require the statistical significance of some network statistic, such as measures of similarity for the properties of interacting nodes. The structure of the network may introduce dependencies among the
Stumpf Michael PH, Thorne Thomas
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