STATISTICAL POWER AND PROBABILITIES OF TYPE I ERROR IN TERMS OF SUITABLE NUMBER OF SIMULATIONS IN NONPARAMETRIC TESTS

Recently, simulation techniques have been widely used in social and medical sciences as well as natural and applied sciences. One of the most common fields of application of these simulation techniques is determination of statistical powers and probabilities of type I error of both parametric and no...

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Autor principal:	Ötüken SENGER
Formato:	article
Lenguaje:	DE EN FR TR
Publicado:	Fırat University 2019
Materias:	number of simulation type i error power of test normal distribution homogeneity of variance. Social Sciences H Social sciences (General) H1-99
Acceso en línea:	https://doaj.org/article/206419cd6611436fa197079785e7d326
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spelling	oai:doaj.org-article:206419cd6611436fa197079785e7d3262021-11-24T09:21:05ZSTATISTICAL POWER AND PROBABILITIES OF TYPE I ERROR IN TERMS OF SUITABLE NUMBER OF SIMULATIONS IN NONPARAMETRIC TESTS2148-416310.9761/jasss_668https://doaj.org/article/206419cd6611436fa197079785e7d3262019-08-01T00:00:00Zhttps://jasstudies.com/index.jsp?mod=tammetin&makaleadi=1546444155_69Senger%20%C3%96t%C3%BCken%20Son-1315-1326.pdf&key=26569https://doaj.org/toc/2148-4163Recently, simulation techniques have been widely used in social and medical sciences as well as natural and applied sciences. One of the most common fields of application of these simulation techniques is determination of statistical powers and probabilities of type I error of both parametric and nonparametric tests. Simulation number plays a vital role in such deterministic studies. In case of number of simulations not being sufficient for a clear analysis, then study findings may be inconsistent and instable. In contrast, if number of simulations exceeds the suitable number then it means waste of time. In this study, the effects of different numbers of simulations on determination process of statistical powers and probabilities of type I error of nonparametric tests were discussed. Furthermore, optimum numbers of simulations for determining statistical powers and probabilities of type I error were suggested for future researchers. In this context, one of the nonparametric tests which is used for testing data obtained from two samples, namely Wald Wolfowitz runs test was applied and results were generalized for all nonparametric tests. In study, four equal and small sample sizes were used, these were as follows: (5, 5), (10, 10), (15, 15) and (20, 20). Simulation runs were performed for twenty different numbers of simulation. Significance level? was assumed as 0, 05 for each sample size. Study was performed by taking the prerequisites of normality and homogeneity of variance into account. According to results; if researchers perform 80.000 simulation runs for a sample size of 5, 60.000 for a sample size of 10 and 50.000 for a sample size of 15 and 40.000 for a sample size of 20 they will have the optimum numbers of simulations in practice.Ötüken SENGERFırat Universityarticlenumber of simulationtype i errorpower of testnormal distributionhomogeneity of variance.Social SciencesHSocial sciences (General)H1-99DEENFRTRJournal of Academic Social Science Studies , Vol 6, Iss 17, Pp 1315-1326 (2019)
institution	DOAJ
collection	DOAJ
language	DE EN FR TR
topic	number of simulation type i error power of test normal distribution homogeneity of variance. Social Sciences H Social sciences (General) H1-99
spellingShingle	number of simulation type i error power of test normal distribution homogeneity of variance. Social Sciences H Social sciences (General) H1-99 Ötüken SENGER STATISTICAL POWER AND PROBABILITIES OF TYPE I ERROR IN TERMS OF SUITABLE NUMBER OF SIMULATIONS IN NONPARAMETRIC TESTS
description	Recently, simulation techniques have been widely used in social and medical sciences as well as natural and applied sciences. One of the most common fields of application of these simulation techniques is determination of statistical powers and probabilities of type I error of both parametric and nonparametric tests. Simulation number plays a vital role in such deterministic studies. In case of number of simulations not being sufficient for a clear analysis, then study findings may be inconsistent and instable. In contrast, if number of simulations exceeds the suitable number then it means waste of time. In this study, the effects of different numbers of simulations on determination process of statistical powers and probabilities of type I error of nonparametric tests were discussed. Furthermore, optimum numbers of simulations for determining statistical powers and probabilities of type I error were suggested for future researchers. In this context, one of the nonparametric tests which is used for testing data obtained from two samples, namely Wald Wolfowitz runs test was applied and results were generalized for all nonparametric tests. In study, four equal and small sample sizes were used, these were as follows: (5, 5), (10, 10), (15, 15) and (20, 20). Simulation runs were performed for twenty different numbers of simulation. Significance level? was assumed as 0, 05 for each sample size. Study was performed by taking the prerequisites of normality and homogeneity of variance into account. According to results; if researchers perform 80.000 simulation runs for a sample size of 5, 60.000 for a sample size of 10 and 50.000 for a sample size of 15 and 40.000 for a sample size of 20 they will have the optimum numbers of simulations in practice.
format	article
author	Ötüken SENGER
author_facet	Ötüken SENGER
author_sort	Ötüken SENGER
title	STATISTICAL POWER AND PROBABILITIES OF TYPE I ERROR IN TERMS OF SUITABLE NUMBER OF SIMULATIONS IN NONPARAMETRIC TESTS
title_short	STATISTICAL POWER AND PROBABILITIES OF TYPE I ERROR IN TERMS OF SUITABLE NUMBER OF SIMULATIONS IN NONPARAMETRIC TESTS
title_full	STATISTICAL POWER AND PROBABILITIES OF TYPE I ERROR IN TERMS OF SUITABLE NUMBER OF SIMULATIONS IN NONPARAMETRIC TESTS
title_fullStr	STATISTICAL POWER AND PROBABILITIES OF TYPE I ERROR IN TERMS OF SUITABLE NUMBER OF SIMULATIONS IN NONPARAMETRIC TESTS
title_full_unstemmed	STATISTICAL POWER AND PROBABILITIES OF TYPE I ERROR IN TERMS OF SUITABLE NUMBER OF SIMULATIONS IN NONPARAMETRIC TESTS
title_sort	statistical power and probabilities of type i error in terms of suitable number of simulations in nonparametric tests
publisher	Fırat University
publishDate	2019
url	https://doaj.org/article/206419cd6611436fa197079785e7d326
work_keys_str_mv	AT otukensenger statisticalpowerandprobabilitiesoftypeierrorintermsofsuitablenumberofsimulationsinnonparametrictests
_version_	1718415214903296000

STATISTICAL POWER AND PROBABILITIES OF TYPE I ERROR IN TERMS OF SUITABLE NUMBER OF SIMULATIONS IN NONPARAMETRIC TESTS

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