Principal Component Factor Analysis of Some Development Factors in Southern Nigeria and Its Extension to Regression Analysis

This study was conducted to evaluate some development factors in Southern Nigeria order ascertain common that explained the interrelationships among them and identify best cities for recommendation. A total sample of 250 from different states three geopolitical zones used this 11 were considered. Kaiser-Meyer-Olkin (KMO) (> 0.5) computed test sampling adequacy; Bartlett’s Test Sphericity (Significant at 0.001) whether correlation between variables are sufficiently large factor analysis; matrix confirm inter-item correlation. In analysis, principal component analysis extraction method. Varimax rotation technique rotation. The result showed new with eigenvalues greater than 1 successfully constructed. accounted 71.63% variance dataset assigned as influencing sustainable Nigeria. communalities results ranging 0.32-0.88 depicted model adequate. extended multiple regression analysis. fitted using scores dependent variable rotated independent variables. coefficient determination,, 99% shows is adequate Nigerian cities. higher estimated scores, better a city. Tolerance VIF values there no multicollinearity model.