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Journals / Süleyman Demirel Üniversitesi Fen Edebiyat Fakültesi Fen Dergisi / 2019 / Cilt: 14 - Sayı: 1

Investigating the Significance of a Correlation Coefficient using Bootstrap Estimates

Bootstrap Tahminini Kullanarak Pearson Korelasyon Katsayısının Önemliliğinin Araştırılması

Tolga ZAMAN
Kamil ALAKUŞ
Pages
77–88
Publication Date
2019-05-31
DOI
—
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AI Summary & Key Takeaways

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

In this study, it is recommended to use the bootstrap method as an alternative to the classical and knife (one exclusion procedure) test statistics in evaluating the significance of the Pearson correlation coefficient by applying the bootstrap method to the simple linear regression model.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Resampling methods offers effective estimates of parameters and its asymptotic distribution.
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Key Findings & Data:In the application, the model parameters, standard errors, Pearson coefficients of correlation, bias and % 95 confidence intervals belonging to bootstrap and jackknife methods in estimated with the help of a real data and the obtained results are interpreted.
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Conclusion & Impact:In this study, it is recommended to use the bootstrap method as an alternative to the classical and knife (one exclusion procedure) test statistics in evaluating the significance of the Pearson correlation coefficient by applying the bootstrap method to the simple linear regression model.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Bootstrap · Çakı · Basit lineer regresyon

Abstract

Resampling methods offers effective estimates of parameters and its asymptotic distribution. In this study, it is recommended to use the bootstrap method as an alternative to the classical and knife (one exclusion procedure) test statistics in evaluating the significance of the Pearson correlation coefficient by applying the bootstrap method to the simple linear regression model. This procedure provides an effective alternative to test the significance of the Pearson correlation coefficient. In the application, the model parameters, standard errors, Pearson coefficients of correlation, bias and % 95 confidence intervals belonging to bootstrap and jackknife methods in estimated with the help of a real data and the obtained results are interpreted. As a result, the test statistic obtained by the bootstrap method is proposed as an alternative to the classical and jackknife test statistics.

Özet

Yeniden örnekleme yöntemleri parametrelerin etkili tahminlerini ve asimptotik dağılımlarını sunar. Bu çalışmada, basit doğrusal regresyon modeline bootstrap yöntemi uygulanarak Pearson korelasyon katsayısının anlamlılığının değerlendirilmesinde klasik ve çakı (birini dışarıda bırak işlemi) test istatistiklerine alternatif olarak bootstrap yönteminin kullanılması önerilmektedir. Bu prosedür Pearson korelasyon katsayısının anlamlılığını test etmek için etkili bir alternatif sağlar. Uygulamada bootstrap ve çakı yöntemlerine ait model parametreleri, standart hatalar, Pearson korelasyon katsayısı, yanlılık ve %95 güven aralığı gerçek bir veri yardımıyla elde edilerek sonuçlar yorumlanmıştır. Sonuçta, bootstrap yöntemi ile elde edilen test istatistiği, klasik ve çakı tabanlı test istatistiğine alternatif bir yöntem olarak önerilmiştir.

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Cite This Article

ZAMAN, T., ALAKUŞ, K. (2019). Investigating the Significance of a Correlation Coefficient using Bootstrap Estimates. Süleyman Demirel Üniversitesi Fen Edebiyat Fakültesi Fen Dergisi, Cilt: 14 - Sayı: 1, 77–88. https://ajindex.com/articles/260941

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