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Journals / Harran Üniversitesi Ziraat Fakültesi Dergisi / 2012 / Cilt: 16 - Sayı: 2

The importance of logistic regression implementations in the Turkish livestock sector and logistic regression implementations /fields

Türkiyede hayvancılık sektöründe lojistik regresyon uygulamalarının önemi lojistik regresyon uygulamaları/alanları

Selami GÜNEY
Şule Yüksel YİĞÎTER
Murat KORKMAZ
Pages
25–36
Publication Date
2022-10-17
DOI
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AI Summary & Key Takeaways

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

Shortly, the applicability of logisticregression in the livestock has been researched.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Logistic regression analysis is one of the mostly preferred regression methods that can beimplemented in modelling binary dependent variables.
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Key Findings & Data:Logistic regression is a mathematicalmodelling approach used to define the relationship between such independent variables as X1,X2, , Xn and Y binary dependent variable which is coded as 0 or 1 for two possible categories.The independent variables may be continuous, discrete, binary or a combination of them.
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Conclusion & Impact:Shortly, the applicability of logisticregression in the livestock has been researched.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Logistic regression analysis is one of the mostly preferred regression methods that can beimplemented in modelling binary dependent variables. Logistic regression is a mathematicalmodelling approach used to define the relationship between such independent variables as X1,X2, , Xn and Y binary dependent variable which is coded as 0 or 1 for two possible categories.The independent variables may be continuous, discrete, binary or a combination of them. In thispaper, logistic regression models are researched. Maximum likelihood methods may be used toestimate the parameters of the logistic model. The interpretations of coefficients are made withodds rate values. In other words, in this paper, the logistic regression analysis has been reviewedthat can define the relationship between the binary result variable and independent variablescomprising of both continuous and discrete variables. Shortly, the applicability of logisticregression in the livestock has been researched.

Özet

Lojistik regresyon analizi ikili bağımlı değişkenleri modellemek için uygulanabilen en çok tercihedilen regresyon metotlarından biridir. Lojistik regresyon X1, X2, , Xn gibi bağımsızdeğişkenleri ile iki olası kategori için O veya 1 gibi kodlanmış Y ikili bağımlı değişkeniarasındaki ilişkiyi tanımlamak için kullanılan matematiksel modelleme yaklaşımıdır. Buradabağımsız değişkenler sürekli, kesikli, ikili veya bunların karışımı olabilir. Bu çalışmada lojistikregresyon modelleri araştırmaktadır. En çok olabilirlik metotları lojistik modelin parametrelerinitahmin etmek için kullanılır. Katsayıların yorumu odds oran değerleriyle yapılır. Bir başkadeyişle bu araştırmada, ikili sonuç değişkeni ile hem sürekli hem de kesikli değişkenlerdenoluşan bağımsız değişkenler kümesi arasındaki ilişkiyi tanımlayabilen lojistik regresyon analiziincelenmiştir. Kısaca, bu çalışmada lojistik regresyonun hayvancılıkta uygulanabilirliği elealınmıştır.

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Cite This Article

GÜNEY, S., YİĞÎTER, Ş. Y., KORKMAZ, M. (2022). The importance of logistic regression implementations in the Turkish livestock sector and logistic regression implementations /fields. Harran Üniversitesi Ziraat Fakültesi Dergisi, Cilt: 16 - Sayı: 2, 25–36. https://ajindex.com/articles/534479

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