In this project, you’ll help a bike rental company enhance its fleet management and pricing strategy by building a daily bike rental forecasting model using time series analysis techniques in R. Your objectives include loading, cleaning, processing, and analyzing daily rental transaction data, and developing and evaluating time series models for the most accurate predictions.
Forecast bikeshare demand using time series models in R
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Objectives
Describe data to answer key questions to uncover insights
Fit well-validated time series models for forecasting future rental bikes demands
Provide analytic insights and data-driven recommendations
Skills you'll demonstrate
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About this Project
Project plan
This project requires you to independently complete the following steps:
Load and explore the data
Create interactive time series plots
Smooth time series data
Decompose and assess the stationarity of time series data
Fit and forecast time series data using ARIMA models
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