Analysis of the Level of Higher Education in China's Provinces Based on Principal Component Analysis and Cluster Analysis

This study employs Principal Component Analysis (PCA) and Cluster Analysis to assess the development levels of higher education across 31 provinces and municipalities in China. Three primary indicators and nine secondary indicators related to higher education levels are selected. These indicators are then reduced to three principal components for ranking purposes. Based on these rankings, the 31 provinces are categorized into four groups according to their varying levels of higher education development. The findings reveal that higher education in China is characterized by an overall low development level, with significant regional imbalances. Furthermore, there is a notable correlation between the level of higher education and the economic development of the provinces. Therefore, the study suggests that China should increase support for underdeveloped regions, focusing on the specific areas in which they are lagging behind, as identified through the principal component rankings.