Topic overview
Time Series Analysis
Time series components, decomposition, benchmark forecasting methods, and practical forecasting workflows in R.
Learning objectives
- •Explain what makes time series data different from cross-sectional data.
- •Identify trend-cycle, seasonal, and remainder components in time series data.
- •Distinguish between additive and multiplicative decomposition.
- •Apply classical decomposition and STL decomposition in R.
- •Build benchmark forecasting models and evaluate them using accuracy measures.
- •Use external data sources such as FRED for time-series exploration.