Two Powerful Tests for Normality

Noughabi, Havva Alizadeh

doi:10.1007/s40745-016-0083-y

Cited by 17 publications

(4 citation statements)

References 27 publications

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“…This test aims to determine whether or not the research data is normally distributed. In parametric statistics, there are two types of normality tests used, the Kolmogorov-Smirnov test and the Shapiro-Wilk test [20].…”

Section: Data Normality Testmentioning

confidence: 99%

Improving Student Achievement Using Flipchart Based Cooperative Learning in Tulungagung

Aziz¹,

Sari²,

Sibilana³

et al. 2020

ujer

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This study aims at improving student learning achievement using flip chart medium design based on cooperative learning method. To prove this goal, this study is focused on (1) knowing the effectiveness of learning media (flip chart) applied to thematic subjects for grade 2 elementary schools in Rejotangan District on student learning outcomes; (2) finding out whether there is an influence of the use of flip chart learning medium on the thematic subjects learning outcomes of grade 2 elementary school students in Rejotangan Districts. The population of this study was 12 elementary school institutions in Rejotangan, Tulungagung subdistrict, by setting 4 schools as samples which were divided into 2 schools as experimental classes (flip chart learning design) and 2 schools as control classes (conventional learning). The sample selection is done using a simple random sampling technique and the data analysis techniques carried out descriptively and inferentially. The results of this study indicate that flip chart learning medium based on cooperative learning method can be said to be quite effective in improving student learning outcomes. This is evidenced by using the N-Gain Score test with a significance level of 62%, while conventional media is not effectively applied to thematic subjects with a percentage of 8%. Furthermore, Mann Whitney test results show that the significance score is 0.00. Therefore, it can be seen that there is a positive influence on the use of flip chart learning medium on learning outcomes in thematic subject of grade 2 elementary school in Tulungagung subdistrict. The results recommend that using cooperative learning with flip chart as a medium is very effective in improving student learning outcomes on thematic subjects of elementary schools lower graders.

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Section: Data Normality Testmentioning

confidence: 99%

Improving Student Achievement Using Flipchart Based Cooperative Learning in Tulungagung

Aziz¹,

Sari²,

Sibilana³

et al. 2020

ujer

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show abstract

“…Different approaches were applied to estimate entropy and based on the new introduced estimators (e.g. modified Vasicek's estimator [37,38], Noughabi's entropy estimator [39]) new goodness-of-fit tests were developed and performances in testing the normal [40][41][42], lognormal [43], uniform [44][45][46], exponential [47], beta [47,48], Poisson [49], Weibull [43], Gamma [43], Pareto [50,51], Student and exponential distribution [52] were studied.…”

Section: Shannon's Entropy Statisticmentioning

confidence: 99%

Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data

Jäntschi

Bolboacă

2017

Ovidius University Annals of Chemistry

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Abstract. Statistical analysis starts with the assessment of the distribution of experimental data. Different statistics are used to test the null hypothesis (H0) stated as Data follow a certain/specified distribution. In this paper, a new test based on Shannon's entropy (called Shannon's entropy statistic, H1) is introduced as goodness-of-fit test. The performance of the Shannon's entropy statistic was tested on simulated and/or experimental data with uniform and respectively four continuous distributions (as error function, generalized extreme value, lognormal, and normal). The experimental data used in the assessment were properties or activities of active chemical compounds. Five known goodness-of-fit tests namely Anderson-Darling, Kolmogorov-Smirnov, Cramér-von Mises, Kuiper V, and Watson U 2 were used to accompany and assess the performances of H1.

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“…Other tests based on the empirical distribution function, less widespread, include the Kuiper test [6], Watson test [7], Cramer-von Mises (CvM) test [8], and the Anderson-Darling (AD) test [9]. From other testing techniques, let us mention ideas based on the empirical characteristic function [10], on the dependence between moments that characterizes normal distributions [11], or on the Noughabi's entropy estimator [12].…”

Section: Introductionmentioning

confidence: 99%

Omnibus test for normality based on the Edgeworth expansion

Wyłomańska

Iskander²,

Burnecki

2020

PLoS ONE

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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. As a result, a number of tests have been proposed in the literature for detecting departures from normality. In this article we develop a novel approach to the problem of testing normality by constructing a statistical test based on the Edgeworth expansion, which approximates a probability distribution in terms of its cumulants. By modifying one term of the expansion, we define a test statistic which includes information on the first four moments. We perform a comparison of the proposed test with existing tests for normality by analyzing different platykurtic and leptokurtic distributions including generalized Gaussian, mixed Gaussian, α-stable and Student's t distributions. We show for some considered sample sizes that the proposed test is superior in terms of power for the platykurtic distributions whereas for the leptokurtic ones it is close to the best tests like those of D'Agostino-Pearson, Jarque-Bera and Shapiro-Wilk. Finally, we study two real data examples which illustrate the efficacy of the proposed test.

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Two Powerful Tests for Normality

Cited by 17 publications

References 27 publications

Improving Student Achievement Using Flipchart Based Cooperative Learning in Tulungagung

Improving Student Achievement Using Flipchart Based Cooperative Learning in Tulungagung

Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data

Omnibus test for normality based on the Edgeworth expansion

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