STATISTICAL ANALYSIS OF THE RELATIONSHIP BETWEEN ATTITUDES TOWARD PUBLIC TRANSPORTATION AND USAGE RATES: A REGRESSION APPROACH

Public transportation plays a crucial role in sustainable urban mobility, yet its usage varies significantly among individuals. This study explores the correlation between individuals' attitudes toward public transportation and their usage rates, aiming to determine whether a positive perception influences increased usage. A quantitative, cross-sectional survey design was employed, with data collected from 156 respondents using a structured questionnaire. The study applied Pearson’s correlation and linear regression analysis to examine the relationship between attitudes and public transport usage. The results indicate a strong positive correlation (r = 0.89, p < 0.001) between attitude and usage rates, with regression analysis showing that attitude significantly predicts public transport usage (β1=1.53, p<0.001\beta_1 = 1.53, p < 0.001). The model's R² value of 0.795 suggests that attitude explains 79.5% of the variance in transport usage. The study instrument demonstrated high reliability (Cronbach’s α = 0.98) and construct validity (0.76). These findings highlight the importance of public perception in increasing ridership, suggesting that policies aimed at improving attitudes toward public transport—such as better service quality, reduced congestion, and environmental awareness campaigns—could effectively boost usage rates. Future research should explore additional factors, such as pricing, accessibility, and personal convenience, to gain a more comprehensive understanding of public transportation behavior.