Moving Average Model
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STATISTICS
Time Series Analysis
Moving Average Model
How past random shocks shape today's data in surprising ways
13 days ago
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Why does the moving average model focus on past error terms rather than past observed values?
Because past observed values are irrelevant in time series analysis.
Because averaging past observed values always provides a better forecast than considering errors.
Because it captures the influence of past random shocks on current values, improving modeling of short-term dependencies.
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MATHEMATICS
Statistics
Moving Average Model
Moving average models reveal hidden patterns in noisy time series data for better forecasting
4 Feb 2026
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What is the primary role of the error terms in a moving average (MA) model in time series analysis?
They are the predicted future values of the time series.
They are constant values that do not change over time.
They represent past random shocks that influence the current value of the series.
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