Bike Sharing Assignment (Linear Regression)
BoomBikes, a US bike-sharing provider, has experienced a revenue drop due to the COVID-19 pandemic. To recover post-lockdown, the company seeks to understand the demand for shared bikes. They have hired a consulting firm to analyze factors affecting bike demand in the American market, aiming to identify significant variables and how they influence demand. By modeling the demand with available data on daily bike usage and related factors, BoomBikes intends to adjust its business strategy to meet customer needs effectively and stand out in the market once the economy stabilizes, ultimately aiming for a strong recovery and increased profits.
Business Objective The goal is to model the demand for shared bikes using various independent variables. This model will help management understand how different factors affect bike demand, allowing them to adjust their business strategy to better meet customer needs and expectations. Additionally, the model will provide insights into demand dynamics in new markets
** Summary - Results **
- All the models are performing very similar to each other
- R^2 is high, which indicates the proportion of the variance in the dependent variable that is predictable from the independent variables.
- Adjusted-R^2 is close to R^2, indicating good performance for the amount of predictors/features used.
- MSE is low, which indicates that the model's predictions are closer to the actual values
- pandas==2.2.2
- numpy==1.26.4
- matplotlib==3.9.1
- seaborn==0.13.2
- sklearn==1.5.1
- statsmodels==0.14.1
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