Dergiler / Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering / 2013 / Cilt: 14 - Sayı: 3

BİR KONUM ÖLÇÜSÜ İLE k BAĞIMSIZ GRUBUN KARŞILAŞTIRILMASI İÇİN BİR TEST

A TEST FOR COMPARING k INDEPENDENT GROUPS WITH A MEASURE OF LOCATION

Sayfa
241–249
Yayın Tarihi
2015-05-04
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

It was fo und that the proposed test copes quite well under normality and homogeneity and it was much more preferable than those two traditional tests under non-normality and heterogeneity of variances

📌 3 Maddede Bu Makale

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Amaç & Hipotez:It is well known that the conventional method for comparing k independent groups, one-way ANOVA F test, depends on normal theory assumptions.
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Temel Bulgular & Veri:The proposed test, ANOV A F test and its rank- based nonparametric counterpart Kruskal-Wallis test were compared in terms of saving nom nal Type I error via Monte Carlo simulations by using moderate sample sizes.
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Sonuç & Katkı:It was fo und that the proposed test copes quite well under normality and homogeneity and it was much more preferable than those two traditional tests under non-normality and heterogeneity of variances
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Budanmış ortalama · Bootstrap-t · Gerçekleşen anlam düzeyi

Abstract

It is well known that the conventional method for comparing k independent groups, one-way ANOVA F test, depends on normal theory assumptions. In this work, a new test is proposed which is based on trimmed means and a bootstrap t method. The proposed test, ANOV A F test and its rank- based nonparametric counterpart Kruskal-Wallis test were compared in terms of saving nom nal Type I error via Monte Carlo simulations by using moderate sample sizes. It was fo und that the proposed test copes quite well under normality and homogeneity and it was much more preferable than those two traditional tests under non-normality and heterogeneity of variances

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Bu Makaleye Atıf Yap

ÖZDEMİR, F., YILDIZTEPE, E. (2015). BİR KONUM ÖLÇÜSÜ İLE k BAĞIMSIZ GRUBUN KARŞILAŞTIRILMASI İÇİN BİR TEST. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, Cilt: 14 - Sayı: 3, 241–249. https://ajindex.com/articles/197061

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Kaynakça (7)

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  2. Bradley, J.V. (1978). Robustness? British Journal of Mathematical and Statistical Psychology, 31, 144-152.
  3. Hoaglin, D.C. (1985). Summerazing Shape Numerically: The g and h Distributions. In D. Hoaglin, F. Mosteller, & J. Tukey (Eds.), Exploring Data Tables, Trends, and Shapes. 461-513. New York: Wiley. Özdemir A.F., Kurt S. (2007). Tek Yönlü Özel Seçimli Varyans Çözümlemesinde Farklı Varyanslılık Sorunu ve Bir Çözüm Önerisi. Anadolu Üniversitesi Bilim ve Teknoloji Dergisi, 8 (1), 93-102.
  4. Staudte, R.G., and Sheater, S.J. (1990). Robust Estimation and Testing. Newyork: Wiley. Ted' Micceri's Web Site. (http://www.freewebs.com/tedstats. Alıntı tarihi: 01.10.2012.)
  5. Wilcox, R.R. (2012). Introduction to Robust Estimation and Hypothesis Testing. Elsevier Academic Press,
  6. Third Edition.
  7. Wilcox, R.R., Charlin, V., Thompson, K.L. (1986). New Monte Carlo Results on The Robustness of The ANOVA F, W and F* Statistics. Communications in Statistics: Simulations and Computations, 15, 933-944.