AVRUPA ÜLKELERİNDEKİ ÜNİVERSİTE ÖĞRENCİLERİNİN GELİR KAYNAKLARI ÜZERİNE BİR FAKTÖR ANALİZİ UYGULAMASI

Yıl 2021, Cilt: 3 Sayı: 1, 16 - 42, 30.06.2021

Oğuzhan Demirel

https://doi.org/10.51541/nicel.846104

Cited By: 1

Öz

Bu istatistiksel çalışma, öğrencilerin gelir kaynaklarını oluşturan gelir türlerini incelemek ve yorumlamak amacıyla yapılmıştır. Bu amaçla, 14 Avrupa ülkesi kullanılarak 9 değişken için tüm verileri içeren bir veri seti oluşturulmuştur. Bu ülkeler, her bir değişken için eksik veri içermedikleri için seçilmiştir. İlk olarak, araştırmanın amacına uygun istatistiksel bir yöntem olan faktör analizi veri setine uygulanmıştır. Daha sonra, açımlayıcı faktör analizi (AFA) yöntemlerinden biri olan temel bileşen analizi (TBA), bu analiz için tercih edilmiştir. Döndürülmüş bileşen matrisi sonuçlarına göre 8 değişken için 3 faktörden oluşan bir sonuç elde edilmiştir. Üniversite öğrencilerinin gelir kaynaklarını oluşturan değişkenlerden oluşan bu faktörler; “öğrencilerin biriktirebileceği gelir”, “öğrencilerin ana gelir kaynakları” ve “öğrencilerin özel gelirleri” olarak adlandırılmıştır.

Anahtar Kelimeler

Öğrencilerin Gelir Kaynakları, Faktör Analizi, Temel Bileşenler Analizi

A FACTOR ANALYSIS APPLICATION ON INCOME SOURCES OF UNIVERSITY STUDENTS IN EUROPEAN COUNTRIES

Öz

This statistical study has been carried out to examine and interpret the income types that make up the income sources of students. For this purpose, a data set has created using 14 European countries that included all the data for 9 variables. These countries have been chosen as they did not contain missing data for each variable. Initially, factor analysis, which is a statistical method suitable for the purpose of the study, has been applied to a data set. Then, principal component analysis (PCA), one of the exploratory factor analysis (EFA) methods, has been preferred for this analysis. According to the rotated component matrix results, a result consisting of 3 factors has been obtained for 8 variables. These factors consisting of variables that make up the income sources of university students; has been named “income that students can save”, “students' main sources of income” and “special incomes of students”.

Anahtar Kelimeler

Students' Income Sources, Factor Analysis, Principal Component Analysis

Kaynakça

• Bartlett, M.C. (1950), Tests of Significance in Factor Analysis, British Journal of Psychology, 3(2), 77-85.
• Christie, H., Munro, M. and Rettig, H. (2001), Making Ends Meet: Student Incomes and Debt, Studies in Higher Education, 26(3), 363-383.
• Dickinson, E.R. and Adelson, J.L. (2016), Choosing Among Multiple Achievement Measures: Applying Multitrait–Multimethod Confirmatory Factor Analysis to State Assessment, ACT, and Student GPA, Data Journal of Advanced Academics, 27(1), 4-22.
• Eurostudent (2017), Composition of Students' Total Monthly Income (Excl. Transfers in Kind), http://database.eurostudent.eu/, Accessed: 27.06.2020.
• Feng, A.L., Wesely, N.C., Hoehle, L.P., Phillips, K.M., Yamasaki, A., Campbell, A.P., Gregorio, L.L., Killeen, T.E., Caradonna, D.S., Meier, J.C., Gray, S.T. and Sedaghat, A.R. (2017), A Validated Model for the 22-item Sino-Nasal Outcome Test Subdomain Structure in Chronic Rhinosinusitis, Int Forum Allergy Rhinol, 7(12), 1140-1148.
• Gwosc, C. and Schwarzenberger, A. (2009), Public/Private Cost-Sharing in Higher Education: an In-Depth Look at the German System Using a Comparative Study, Journal of Higher Education Policy and Management, 31(3), 239-249.
• Hair, J.F., Anderson, R.E., Tatham, R.L. and Black, W.C. (1998), Multivariate Data Analysis, Prentice Hall, New Jersey.
• Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. and Tatham, R.L. (2006), Multivariate Data Analysis (6th Edition). Upper Saddle River: Pearson Prentice Hall, New Jersey.
• Horn, R.A. and Johnson, C.R. (1985), Topics in Matrix Analysis, Cambridge University Press, Cambridge.
• Hoxby, C. and Turner, S. (2013), Expanding College Opportunities for High-Achieving, Low Income Students, Stanford Institute For Economic Policy Research Discussion Paper No. 12-014, 1-37.
• Ian T.J. (1995), Rotation of Principal Components: Choice of Normalization Constraints, Journal of Applied Statistics, 22(1), 29-35.
• Jolliffe, I., Trendafilov, N. and Uddin, M. (2003), A Modified Principal Component Technique Based on the LASSO. Journal of Computational and Graphical Statistics, 12(3), 531-547.
• Kaiser, H.F. (1970), A Second-Generation Little Jiffy, Psychometrika, 35(4), 401-415.
• Karadeniz, Ş. (2012), Development of Student Satisfaction on Blended Learning Questionnaire, Electronic Journal of Social Sciences, 11(40), 161-172.
• Karataş, H. and Fer, S. (2011), CIPP Evaluation Model Scale: Development, Reliability and Validity, Procedia Social and Behavioral Sciences, 15, 592-599.
• Leech, N.L., Barrett, K.C. and Morgan, G.A. (2005), SPSS for Intermediate Statistics: Use and Interpretation, Psychology Press, London.
• Martínez-García M.A., Perpiñá-Tordera M., Soler-Cataluña J.J., Román-Sánchez P., Lloris-Bayo A. and González-Molina A. (2007), Dissociation of Lung Function, Dyspnea Ratings and Pulmonary Extension in Bronchiectasi, Respir Med., 101(11), 2248-2253.
• Meyers, L.S., Gamst, G. and Guarino, A.J. (2006). Applied Multivariate Research: Design and Interpretation, Sage, California.
• Muthén, B. (1991), Multilevel Factor Analysis of Class and Student Achievement Components, Journal of Educational Measurement, 28(4), 338-354.
• Pengpid, S., Peltzer, K., Kassean, H.K., Tsala Tsala, J.P., Sychareun, V. & Müller-Riemenschneider, F. (2015), Physical Inactivity and Associated Factors Among University Students in 23 Low-, Middle- and High-Income Countries, International Journal of Public Health, 60(5), 539-549.
• Pengpid, S. and Peltzer, K. (2018), Vigorous Physical Activity, Perceived Stress, Sleep and Mental Health Among University Students From 23 Low- and Middle-Income Countries, International Journal of Adolescent Medicine and Health, 32(2), 1-7.
• Russell, D.W. (2002), In Search of Underlying Dimensions: The Use (and Abuse) of Factor Analysis in Personality and Social Psychology Bulletin, Personality and Social Psychology Bulletin, 28(12), 1629-1646.
• Spearman, C. (1904), General Intelligence Objectively Determined and Measured, The American Journal of Psychology, 15(2), 201-293.
• Stufflebeam, D.L. and Webster, W.J. (1988), Evaluation as an Administrative Function. In N. Boyan (Ed.), Handbook of Research on Educational Administration (pp. 569-601), White Plains, New York.
• Suhr, D.D. (2006), Exploratory or Confirmatory Factor Analysis? Presented: San Francisco, CA, SAS Users Group International Conference (SUGI31).
• Şencan, H. (2005), Sosyal ve Davranışsal Ölçümlerde Güvenilirlik ve Geçerlilik (Birinci Baskı), Seçkin Yayınları, Ankara.
• Tabachnick, B.G. and Fidell, L.S. (2013), Using Multivariate Statistics (6th Edition). Pearson Education Limited, London.
• Tatlıdil, H. (2002), Uygulamalı Çok Değişkenli İstatistiksel Analiz, Akademi Matbaası, Ankara.
• Turanlı, M., Taşpınar-Cengiz, D. and Bozkır, Ö. (2014), Faktör Analizi ile Üniversiteye Giriş Sınavlarındaki Başarı Durumuna Göre İllerin Sıralanması, Istanbul University Econometrics and Statistics e-Journal, 0(17), 45-68.