Correlation analysis and regression of transit ridership by means of public buses – A preliminary data analysis

Abstract Given ever-increasing private transportation ownership, a rising population, and unceasing mobility, it is crucial to ensure the usage improvement of public services. Therefore, important review understand relationships between variables affecting ridership boost them. This paper acts as preliminary data analysis in which correlation multiple linear regression (MLR) analyses were constructed examine bus transit ridership. The main goal this study identify that influence degree they do so during a) peak hours b) off-peak hours. Independent such commercial speed, service frequency, in-vehicle travel time, stop distance, rainfall employed study. Results show all independent are significant correlated with However, models distance time not statistically hours, respectively. findings recommend creation relevant policy initiatives can assist agencies increasing by analysing predictive factors. Additionally, output from be used future works on designing efficient routes, locations, even schedules.