How to Handle Seasonality in Time Series Analysis?
Seasonality refers to periodic fluctuations in time series data, often driven by external factors such as weather or human behavior patterns. To handle seasonality, methods like Seasonal ARIMA (SARIMA) or STL decomposition can be employed. These techniques account for seasonal variations and provide a clearer understanding of the underlying trends.
