An Analysis of the Relationship Between Educational Attainment and Employment Based on Statistical Methods

This study employs statistical methods to analyze the relationship between educational attainment and employment, aiming to explore the differences in employment patterns, industry distribution, and employment stability across different education levels. Using data from Review of Educational Economics, the research integrates three analytical approaches: analysis of variance (ANOVA), chi-square test, and K-means cluster analysis. This essay explores how education influences employment patterns amid global educational expansion and a shifting job market. The results show significant differences in employment continuity: the average employment score in the tertiary education group is 3.52 (SD = 0.89), compared to 2.89 (SD = 1.21) in the non-tertiary group, with a moderate effect size (Cohen's d = 0.62). Chi-square analysis shows tertiary-educated individuals dominate finance/technology sectors (35%), while non-tertiary groups concentrate in service industries (45%). Cluster analysis identifies three groups: highly educated stable employees (37.46%), secondary-educated part-timers (33.94%), and transitional workers (28.60%), highlighting disparities in job security. The study confirms education’s "signaling effect" in employer screening and its role in formal/informal job market access. Results inform policy adjustments, educational resource allocation, and practice-oriented curricula to enhance employment alignment and quality.