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Journals / Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi / 1984 / Sayı: 6

ÇOKLU DOĞRUSAL BAĞINTININ ÖLÇÜLMESİ SORUNU

Mansur Atalay
Pages
97–106
Publication Date
1984-01-01
DOI
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AI Summary & Key Takeaways

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

To look at the simple correlations between the explanatory variables in the model is proposed as the best way of the detection of multicollinearity.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, mullicollinearty problem is discus-sed and some detection methods for multicollinea-rity are introduced.
📊
Key Findings & Data:These detection methods are applied to the regression analysis which estimates Turkish agricultural product.
💡
Conclusion & Impact:To look at the simple correlations between the explanatory variables in the model is proposed as the best way of the detection of multicollinearity.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:çoklu doğrusal bağıntının ülçülmesi · ekonometri

Özet

In this study, mullicollinearty problem is discus-sed and some detection methods for multicollinea-rity are introduced. These detection methods are applied to the regression analysis which estimates Turkish agricultural product. To look at the simple correlations between the explanatory variables in the model is proposed as the best way of the detection of multicollinearity.

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Cite This Article

Atalay, M. (1984). ÇOKLU DOĞRUSAL BAĞINTININ ÖLÇÜLMESİ SORUNU. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Sayı: 6, 97–106. https://ajindex.com/articles/119512

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References (12)

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