Faktör Analizinde Faktör Döndürme Yöntemleri: Ziraat Verisi Üzerinde Bir Uygulama

Abstract

Bu çalışmada, çok değişkenli analiz yöntemlerinden biri olan faktör analizinde döndürme aşaması incelenmiştir. Faktör analizinin tüm aşamaları tanımlanmıştır. Çalışmanın materyali, 9 değişken içeren 20 parsele (tekrarlama) ekilen arpadan elde edilen bir veri setinden oluşmaktadır. Her parselde, o parselde seçilen 6 bitkinin ortalaması kullanılmıştır. Çalışmada vurgulanan değişkenler bitki boyu, yaprak sayısı, başak uzunluğu, başak ağırlığı, tane verimi, çiçeklenme periyodu (gün), hasat indeksi, verim ve 1000 tane ağırlığıdır. Analizin ön koşullarını sağlayan veri setinden, faktör çıkarma yöntemi olan temel bileşen analizi ile faktörler elde edilmiştir. Farklı faktör döndürmeler için kullanılan kriterler verilmiş ve bu kriterlere dayanarak her veri seti için en uygun döndürme açısını veren formül elde edilmiştir. Sonuç olarak, orthomax, varimax, quartimax ve equamax için elde edilen formüller veri setinden elde edilen faktörlere uygulanmış ve sonuçlar yorumlanmıştır. Faktör döndürme sonucunda varimax, quartimax ve equamax yöntemleri kullanıldığında değişkenlerin faktör yükleri açısından değerleri her faktörde farklılık göstermiştir. Bu, faktör analizi sonuçları için arzu edilen bir durumdur.

Keywords

• Equamax
• faktör analizi
• orthomax
• döndürme yöntemleri
• varimax
• quartimax

Factor Rotation Methods in Factor Analysis: An Application on Agricultural Data

Abstract

In this study, the rotation stage of factor analysis, which is one of the multivariate analysis methods, was examined. All stages of factor analysis have been defined. The material of the study consisted of a data set obtained from barley planted in 20 plots (replication) having 9 variables. In each plot, the average of 6 plants selected from that plot was used. The variables emphasized in the study were plant height, number of leaves, spike length, spike weight, grain yield, flowering period (days), harvest index, yield, and 1000-grain weight. Factors were obtained by principal component analysis, which is a factor extraction method, from the data set that met the prerequisites of the analysis. The criteria used in different factor rotations are given and based on these criteria, the formula that gives the optimum rotation angle for each data set was obtained. As a result, the formulas obtained for orthomax, varimax, quartimax, and equamax were applied to the factors obtained from the data set and the results were interpreted. As a result of factor rotation, when varimax, quartimax, and equamax methods were used, the values of the variables in terms of factor loads differed in each factor. This is a desirable situation for factor analysis results.

Keywords

• Equamax
• factor analysis
• orthomax
• rotation methods
• varimax
• quartimax

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