Which category includes both Multiple Regression and Seasonal Exponential Smoothing?

Which category includes both Multiple Regression and Seasonal Exponential Smoothing?

• A. Horizontal Sec Trend & Seasonality
• B. Positive/Negative Sec Trend & No Seasonality
• C. Non Linear Trends
• D. Episodic Variation

Answer: (D)

Focus on how the data changes in irregular, event-driven ways. Episodic variation covers those irregular fluctuations that aren’t explained by a simple upward or downward trend or by a fixed seasonal pattern. Multiple Regression handles this by using external predictors or dummy variables for specific events, holidays, promotions, or other shocks, so the model can attribute moves in the data to those episodes. Seasonal Exponential Smoothing, while built to capture regular seasonal patterns, also updates its components as new data come in, which allows it to adapt to deviations from past patterns that occur in episodes. Because both approaches are capable of explaining and adapting to those irregular, episodic fluctuations rather than only a smooth trend or fixed seasonality, they’re categorized under episodic variation.

Focus on how the data changes in irregular, event-driven ways. Episodic variation covers those irregular fluctuations that aren’t explained by a simple upward or downward trend or by a fixed seasonal pattern. Multiple Regression handles this by using external predictors or dummy variables for specific events, holidays, promotions, or other shocks, so the model can attribute moves in the data to those episodes. Seasonal Exponential Smoothing, while built to capture regular seasonal patterns, also updates its components as new data come in, which allows it to adapt to deviations from past patterns that occur in episodes. Because both approaches are capable of explaining and adapting to those irregular, episodic fluctuations rather than only a smooth trend or fixed seasonality, they’re categorized under episodic variation.