When applying a moving average model in time series analysis, what does the moving average primarily smooth out?
- Outliers
- Random fluctuations or noise
- Seasonality
- Trend
A moving average primarily smooths out random fluctuations or noise in time series data. This helps highlight underlying patterns and trends by reducing the impact of short-term, erratic movements.
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