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Journals / Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi / 2017 / Cilt: 32 - Sayı: 2

Aynı Olmayan Dağılımlar Altında Konum Eşitlik Testleri

Tests of Location Equality under Non-Identical Distributions

İrem YILMAZ
Gözde NAVRUZ
A. Fırat ÖZDEMİR
Pages
1–13
Publication Date
2022-10-11
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The newly proposedmethod outperformed ANOVA-F and other alternatives under various situations.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The ANO VA-F test is the most known procedurefor comparing at least three populationmeans.
📊
Key Findings & Data:In this study, Welch ’s test with trimmed mean, Welch ’s test withtrimmed mean and bootstrap-t, newly proposed 3: test and ANOVA-F test werecompared in terms of actual Type error rates under not only non-normality andheteroscedasticity, but also with non-identical distribution shapes.
💡
Conclusion & Impact:The newly proposedmethod outperformed ANOVA-F and other alternatives under various situations.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The ANO VA-F test is the most known procedurefor comparing at least three populationmeans. However, this conventional test might give misleading results when it’s underlyingassumptions are violated. In this study, Welch ’s test with trimmed mean, Welch ’s test withtrimmed mean and bootstrap-t, newly proposed 3: test and ANOVA-F test werecompared in terms of actual Type error rates under not only non-normality andheteroscedasticity, but also with non-identical distribution shapes. The newly proposedmethod outperformed ANOVA-F and other alternatives under various situations.

Özet

ANOVA-F testi, en az üç kitle ortalamasının karşılaştırılması için en çok bilinenyöntemdir. Ancak, bu geleneksel yöntem varsayımları ihlal edildiğinde yanıltıcı sonuçlarverebilir. Bu çalışmada budanmış ortalama ile Welch testi, budanmış ortalama vebootstrap--t ile Welch testi, yeni önerilen B; testi ve ANOVA--F testi gerçekleşen 1. Tip hataoranlarına göre, sadece normalliğin ve homojen varyanslılığın sağlanmadığı durumlardadeğil, aynı zamanda aynı olmayan dağılım şekilleri altında da karşılaştırılmıştır. Yeniönerilen yöntem, ANOVA--F ve diğer alternatiflere göre farklı durumlar altında daha iyisonuçlar vermiştir.

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Cite This Article

YILMAZ, İ., NAVRUZ, G., ÖZDEMİR, A. F. (2022). Aynı Olmayan Dağılımlar Altında Konum Eşitlik Testleri. Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Cilt: 32 - Sayı: 2, 1–13. https://ajindex.com/articles/490520

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