How are forecasting techniques like ARIMA, SARIMA, and Prophet used in time series analysis?Review LaterThey are used to estimate the mean and variance of a time series.They are used to identify outliers and anomalies in a time series.They are used to cluster similar time series together.They are used to make future predictions based on historical patterns in a time series.

Which of the following is NOT a commonly used forecasting technique for time series data?Review LaterARIMASARIMAProphetLinear Regression

What does ARIMA stand for in time series forecasting?Average Regression Impacted Moving AverageAuto-Regressive Integral Moving AverageAuto-Regressive Increased Mean AdjustmentAdvanced Regression Integral Model Assessment

Why is stationarity important in time series analysis?Review LaterStationarity simplifies the modeling process.Stationarity reduces the computational complexity.Stationarity guarantees accurate forecasting.Stationarity allows for the inclusion of external factors.

What does time series analysis mean?

Which method is often used for long-term energy forecasting to account for future changes in energy policies, technology advancements, and socioeconomic factors?*a) Scenario analysisb) Time series analysisc) Exponential smoothingd) Moving average forecasting