Journals / Öneri Dergisi / 2002 / Cilt: 5 - Sayı: 18

HAYAT VE HAYAT DIŞI SİGORTA ŞİRKETLERİNİN ÇOK DEĞİŞKENLİ İSTATİSTİKSEL YÖNTEMLERLE KARŞILAŞTIRILMASI

Pages
147–154
Publication Date
2002-06-28
DOI
—
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AI Summary & Key Takeaways

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

As a result, most critical factor for discriminating the life branch and nonlife branch insurance company is found to be the factor of reserves.

📌 3 Key Takeaways

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Objective & Hypothesis:The Aim of this paper is to decide on which factors are effective on insurance companies for the life branch and nonlife branch.
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Key Findings & Data:To find out this factor, discriminant and logistic regression analysis are used in this paper.
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Conclusion & Impact:As a result, most critical factor for discriminating the life branch and nonlife branch insurance company is found to be the factor of reserves.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Hayat sigorta şirketleri · Hayat dışı sigorta şirketleri · Çok değişkenli istatiksel yöntem

Özet

The Aim of this paper is to decide on which factors are effective on insurance companies for the life branch and nonlife branch. To find out this factor, discriminant and logistic regression analysis are used in this paper. Starting with thirty variables, some of the irrelevant variable are removed and factor analysis is applied to the remained thirteen variables. Using factor analysis on thirteen variables, two factors called profit factor and the reserve factor are obtained. Then, discriminant and logistic regression analysis are applied to new variables and results are compared. As a result, most critical factor for discriminating the life branch and nonlife branch insurance company is found to be the factor of reserves.

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Cite This Article

ALTAŞ, D. (2002). HAYAT VE HAYAT DIŞI SİGORTA ŞİRKETLERİNİN ÇOK DEĞİŞKENLİ İSTATİSTİKSEL YÖNTEMLERLE KARŞILAŞTIRILMASI. Öneri Dergisi, Cilt: 5 - Sayı: 18, 147–154. https://ajindex.com/articles/36195

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References (13)

  1. TATLIDİL, H., Uygulamalı Çok Değişkenli İstatistiksel Analiz, Ankara, 1992, s.214
  2. ZINKMUND, W.G., Exploring Marketing Research, Fifth Edition, Orlando, 1994, s.690-692
  3. HAIR,J.F.; ANDERSON, R.E.; TATHAM, R.L., Multivariate Data Analysis With Reading, Newyork, 1990, s.75, 233-235
  4. GREEN, F.E.; TULL, D.S., Research For Marketing Decisions, Fourth Edition, New Jersey, 1978, s.429
  5. COOOLEY, W.W.; LOHNES, P.R., Multivariate Data Analysis, Toronto, 1971, s.146-147
  6. MCDANIEL, C.Jr.; GATES, R., Contemporary Marketing Research, Third Edition, San Francisco, 1996, s.612
  7. ÖZDAMAR, K., Paket Programlar İle İstatistiksel Veri Analizi l-lI, Eskişehir, 1999, s.317-320
  8. LEHMANN, RD.; GUPTA, S.; STECKEL, H.J., Marketing Research, Amsterdam, 1998, s.691, 697, 709
  9. GÜRİŞ, S.; ÇAĞLAYAN, E., Ekonometrinin Temelleri, Der Yayınları, İstanbul, 2000, s.652
  10. AKKAYA, Ş.; PAZARLIOĞLU, V.M., Ekonometri-II, İstanbul, 1998, s.78
  11. GUJARATI, N. Damodar, Çevirenler: Ümit Şenesen, Gülay Şenesen, Temel Ekonometri, Literatür Yayıncılık, İstanbul, 1999, s.542,554-556
  12. FOX, J., Applied Regression Analysis, Linear Models And Related Methods, Sage Pub., London, 1997, s.440,442
  13. PINDYCK, S.R.; RUBINFELD, L.D., Econometric Models And Economic Forecasts, McGraw-Hill, Newyork, 1998, s.329-330.