Case Study: Analyzing City Time Series Data in R

The Korshub Take

This intermediate R case study applies time series analysis techniques to diverse urban datasets from the city of Boston. Through interactive exercises, you will examine temporal patterns across municipal flight schedules, weather trends, economic indicators, and local sports team statistics.

Who It\'s For

R programmers, data analysts, and quantitative researchers who want practical experience applying time series forecasting and decomposition to real-world municipal datasets.

Key Takeaways

• Time Series Formatting: Structure time-indexed urban data in R for temporal analysis and visual inspection.
• Trend & Seasonality Decomposition: Deconstruct municipal weather, flight, and economic data into trend, seasonal, and residual components.
• Comparative Urban Analysis: Evaluate correlations across distinct city metrics over time, such as weather shifts and event schedules.
• Applied Time Series Modeling: Gain practical experience manipulating time series objects to solve urban data challenges.