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Time Series Analysis Flashcards

7 cards from real Data Science practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

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  1. In time series analysis, a series is considered stationary if:

    Answer: Its mean, variance, and autocovariance are constant over time

    A stationary time series has constant statistical properties (mean, variance, and autocovariance) over time, which is required by most classical time series models.

  2. What does the Autocorrelation Function (ACF) measure in a time series?

    Answer: The correlation between a time series and a lagged version of itself

    The ACF measures the linear correlation between a time series and its own past values at various lags, helping identify repeating patterns and appropriate model parameters.

  3. What does the 'I' stand for in the ARIMA model?

    Answer: Integrated

    The 'I' in ARIMA stands for 'Integrated,' referring to the differencing of the series to achieve stationarity before fitting the AR and MA components.

  4. What is seasonality in a time series?

    Answer: Regular, periodic patterns that repeat at fixed time intervals

    Seasonality refers to regular, repeating fluctuations that occur at fixed intervals such as daily, weekly, or yearly cycles — driven by factors like weather or business calendars.

  5. The Partial Autocorrelation Function (PACF) is primarily used to determine:

    Answer: The order of the Autoregressive (AR) component

    PACF measures the direct correlation between a series and its lags after removing the effect of intermediate lags, which helps identify the appropriate AR order (p) in ARIMA.

  6. What is white noise in time series analysis?

    Answer: A series of uncorrelated random variables with constant mean and variance

    White noise is a sequence of uncorrelated random variables with zero mean and constant variance — it contains no predictable structure and represents the ideal model residuals.

  7. What does 'trend' represent in a time series?

    Answer: The long-term increase or decrease in the data over an extended period

    Trend represents the long-term, systematic directional movement (upward or downward) in the data, distinct from seasonal cycles or random noise.