Moving averages, exponential smoothing, trend and seasonality, forecast accuracy.
40 cards · basic cards · AI-written, checked twice. Edit anything.
- What is a simple moving average?
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The average of the previous n observations, where all observations are weighted equally- What is the main advantage of a weighted moving average?
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It allows more recent observations to have higher weights than older observations- Define exponential smoothing
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A forecasting method where recent observations receive higher weights and weights decay exponentially into the past- What does the smoothing parameter alpha control in exponential smoothing?
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The weight given to the most recent observation, ranges from 0 to 1- What is Holt's double exponential smoothing?
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An extension of simple exponential smoothing that estimates both level and trend components- What does Winter's triple exponential smoothing add to Holt's method?
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A seasonal component in addition to level and trend- What is trend in a time series?
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A persistent, long-term movement in one direction, either upward or downward- What is seasonality in a time series?
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A repeating pattern that occurs at fixed intervals within each year or defined period- What is additive seasonality?
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A seasonal component that is added to the level and trend, producing constant seasonal swings- What is multiplicative seasonality?
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A seasonal component that multiplies the level and trend, producing larger seasonal swings when the trend is higher- When should multiplicative seasonality be used instead of additive?
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When the seasonal variation increases or decreases proportionally with the level of the series- What does stationarity mean in a time series?
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The statistical properties (mean, variance, autocorrelation) remain constant over time- What is differencing?
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Subtracting each observation from the previous observation to remove trend and make a series stationary- What does an ACF plot show?
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The correlation between an observation and its lagged values at different lags- What does a PACF plot show?
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The correlation between an observation and its lagged values after removing the effects of intermediate lags
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