This repository contains the code and reports for the statistical analysis of BIXI Montreal's bike-sharing system data. The analysis focuses on understanding the factors that influence trip duration, revenue, and overall usage based on the 2021 season's data.
The project is divided into four parts, each aimed at exploring different statistical models and providing insights into BIXI's trip and revenue data.
The dataset includes details on BIXI rentals such as start/end time, stations, trip duration, user type (member or non-member), and weather conditions.
- Part1-Exploratory analysis: Initial data exploration to understand the variables and their relationships.
- Part2-Linear regression models: Analysis using linear regression to investigate trip duration and revenue.
- Part3-Generalized linear models: Use of generalized linear models to study the number of rentals and the average trip duration.
- Part4-Linear mixed models: Advanced modeling to account for potential correlations within stations.