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Quantile-Zone Based Approach to Normality Testing
Mathematics, 2022 Normality testing remains an important issue for researchers, despite many solutions that have been published and in use for a long time. There is a need for testing normality in many areas of research and application, among them in Quality control, or ...
Atif Avdović, Vesna Jevremović
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Neutrosophic D’Agostino Test of Normality: An Application to Water Data
Journal of Mathematics, 2021 The D’Agostino test has been widely applied for testing the normality of the data. The existing D’Agostino test cannot be applied when the data have some indeterminate observations or observations which are obtained from the complex systems.
Mohammed Albassam +2 more
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International Journal of Assessment Tools in Education, 2022 This study aims to compare normality tests in different sample sizes in data with normal distribution under different kurtosis and skewness coefficients obtained simulatively.
Süleyman Demir
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Testing normality: a GMM approach [PDF]
Journal of Econometrics, 2005 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bontemps, Christian, Meddahi, Nour
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Results of normality test (Anderson-Darling normality test).
, 2021 Results of normality test (Anderson-Darling normality test).
Sang Ok Choi (11426728) +2 more
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More about the basic assumptions of t-test: normality and sample size [PDF]
Korean Journal of Anesthesiology, 2019 Most parametric tests start with the basic assumption on the distribution of populations. The conditions required to conduct the t-test include the measured values in ratio scale or interval scale, simple random extraction, normal distribution of data ...
Tae Kyun Kim, Jae Hong Park
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Test and asymptotic normality for mixed bivariate measure
Statistica, 2013 Consider a pair of random variables whose joint probability measure is the sum of an absolutely continuous measure, a discrete measure and a finite number of absolutely continuous measures on some lines called jum lines.
Rachid Sabre
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Omnibus test for normality based on the Edgeworth expansion.
PLoS ONE, 2020 Statistical inference in the form of hypothesis tests and confidence intervals often assumes that the underlying distribution is normal. Similarly, many signal processing techniques rely on the assumption that a stationary time series is normal.
Agnieszka Wyłomańska +2 more
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A New Goodness of Fit Test for Multivariate Normality and Comparative Simulation Study
Mathematics, 2021 The testing of multivariate normality remains a significant scientific problem. Although it is being extensively researched, it is still unclear how to choose the best test based on the sample size, variance, covariance matrix and others.
Jurgita Arnastauskaitė +2 more
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