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Lag ACF PACF Part5

Unlock the secrets of time series modeling in this video! We’ll explore key concepts: Lag: Understand how past observations impact future ones. ACF (AutoCorrelation Function): Peek into the correlation between a data point and its lagged versions. PACF (Partial AutoCorrelation Function): Unravel direct relationships between data points, minus the influence of intermediate lags. But that’s not all! I’ll guide you on the detective work to choose the right model: AR (AutoRegressive): When lagged values matter—like a time-traveling Sherlock. MA (Moving Average): For capturing short-term fluctuations—our data sleuth’s magnifying glass. ARMA (AutoRegressive Moving Average): The dynamic duo of AR and MA, solving mysteries together. ARIMA (AutoRegressive Integrated Moving Average): Handling trends and seasonality like seasoned detectives. SARIMA (Seasonal ARIMA): When the case involves seasonal patterns—our seasoned investigators.