9. Time Series & Sequential Data Flashcards

1
Q

What is a time series?

A

A sequence of observations recorded at regular time intervals.

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2
Q

What is stationarity in time series?

A

A time series is stationary if its statistical properties (mean, variance) do not change over time.

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3
Q

What is the difference between additive and multiplicative seasonality?

A

Additive seasonality means variations are constant over time, while multiplicative means they increase or decrease with the trend.

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4
Q

What is differencing in time series?

A

A technique used to remove trends by computing the difference between consecutive observations.

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5
Q

What is an autoregressive (AR) model?

A

A model where future values depend on previous values plus noise.

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6
Q

What is a moving average (MA) model?

A

A model where future values depend on past forecast errors.

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7
Q

What is an ARMA model?

A

A combination of autoregressive (AR) and moving average (MA) models.

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8
Q

What is an ARIMA model?

A

A model combining autoregression, differencing, and moving averages for forecasting.

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9
Q

What is a seasonal ARIMA (SARIMA) model?

A

An extension of ARIMA that includes seasonal components.

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10
Q

What is exponential smoothing?

A

A forecasting technique that applies weighted averages to past data points.

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11
Q

What is Holt-Winters method?

A

A time series forecasting technique that accounts for trend and seasonality.

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12
Q

What is a rolling window in time series analysis?

A

A method of computing statistics over a sliding window of past observations.

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13
Q

What is a lag variable?

A

A past value of a time series used as a predictor for the current value.

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14
Q

What is Granger causality?

A

A statistical hypothesis test to determine if one time series can predict another.

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15
Q

What is a cointegration test?

A

A test used to determine if two or more time series have a long-term relationship.

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16
Q

What is a structural break in time series?

A

A sudden change in the relationship between time series variables.

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17
Q

What is seasonality in time series?

A

A repeating pattern of fluctuations over a fixed period.

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18
Q

What is a trend in time series?

A

A long-term increase or decrease in data values over time.

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19
Q

What is forecasting?

A

The process of predicting future values based on historical data.

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20
Q

What is autocorrelation?

A

The correlation of a time series with its past values.

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21
Q

What is partial autocorrelation?

A

The correlation of a time series with its past values after removing intermediate dependencies.

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22
Q

What is the ACF (Autocorrelation Function)?

A

A function that measures how a time series is correlated with its past values.

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23
Q

What is the PACF (Partial Autocorrelation Function)?

A

A function that shows the direct relationship between a time series and its lags.

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24
Q

What is white noise in time series?

A

A sequence of random values with a constant mean and variance and no correlation between observations.

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25
Q

What is a random walk?

A

A time series model where each step is randomly determined, often used in financial markets.

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26
Q

What is a unit root?

A

A characteristic of non-stationary time series where shocks have a permanent effect.

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27
Q

What is the Augmented Dickey-Fuller (ADF) test?

A

A statistical test used to determine whether a time series is stationary.

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28
Q

What is a time series?

A

A sequence of observations recorded at regular time intervals.

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29
Q

What is stationarity in time series?

A

A time series is stationary if its statistical properties (mean, variance) do not change over time.

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30
Q

What is the difference between additive and multiplicative seasonality?

A

Additive seasonality means variations are constant over time, while multiplicative means they increase or decrease with the trend.

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31
Q

What is differencing in time series?

A

A technique used to remove trends by computing the difference between consecutive observations.

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32
Q

What is an autoregressive (AR) model?

A

A model where future values depend on previous values plus noise.

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33
Q

What is a moving average (MA) model?

A

A model where future values depend on past forecast errors.

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34
Q

What is an ARMA model?

A

A combination of autoregressive (AR) and moving average (MA) models.

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35
Q

What is an ARIMA model?

A

A model combining autoregression, differencing, and moving averages for forecasting.

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36
Q

What is a seasonal ARIMA (SARIMA) model?

A

An extension of ARIMA that includes seasonal components.

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37
Q

What is exponential smoothing?

A

A forecasting technique that applies weighted averages to past data points.

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38
Q

What is Holt-Winters method?

A

A time series forecasting technique that accounts for trend and seasonality.

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39
Q

What is a rolling window in time series analysis?

A

A method of computing statistics over a sliding window of past observations.

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40
Q

What is a lag variable?

A

A past value of a time series used as a predictor for the current value.

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41
Q

What is Granger causality?

A

A statistical hypothesis test to determine if one time series can predict another.

42
Q

What is a cointegration test?

A

A test used to determine if two or more time series have a long-term relationship.

43
Q

What is a structural break in time series?

A

A sudden change in the relationship between time series variables.

44
Q

What is seasonality in time series?

A

A repeating pattern of fluctuations over a fixed period.

45
Q

What is a trend in time series?

A

A long-term increase or decrease in data values over time.

46
Q

What is forecasting?

A

The process of predicting future values based on historical data.

47
Q

What is autocorrelation?

A

The correlation of a time series with its past values.

48
Q

What is partial autocorrelation?

A

The correlation of a time series with its past values after removing intermediate dependencies.

49
Q

What is the ACF (Autocorrelation Function)?

A

A function that measures how a time series is correlated with its past values.

50
Q

What is the PACF (Partial Autocorrelation Function)?

A

A function that shows the direct relationship between a time series and its lags.

51
Q

What is white noise in time series?

A

A sequence of random values with a constant mean and variance and no correlation between observations.

52
Q

What is a random walk?

A

A time series model where each step is randomly determined, often used in financial markets.

53
Q

What is a unit root?

A

A characteristic of non-stationary time series where shocks have a permanent effect.

54
Q

What is the Augmented Dickey-Fuller (ADF) test?

A

A statistical test used to determine whether a time series is stationary.

55
Q

What is a time series?

A

A sequence of observations recorded at regular time intervals.

56
Q

What is stationarity in time series?

A

A time series is stationary if its statistical properties (mean, variance) do not change over time.

57
Q

What is the difference between additive and multiplicative seasonality?

A

Additive seasonality means variations are constant over time, while multiplicative means they increase or decrease with the trend.

58
Q

What is differencing in time series?

A

A technique used to remove trends by computing the difference between consecutive observations.

59
Q

What is an autoregressive (AR) model?

A

A model where future values depend on previous values plus noise.

60
Q

What is a moving average (MA) model?

A

A model where future values depend on past forecast errors.

61
Q

What is an ARMA model?

A

A combination of autoregressive (AR) and moving average (MA) models.

62
Q

What is an ARIMA model?

A

A model combining autoregression, differencing, and moving averages for forecasting.

63
Q

What is a seasonal ARIMA (SARIMA) model?

A

An extension of ARIMA that includes seasonal components.

64
Q

What is exponential smoothing?

A

A forecasting technique that applies weighted averages to past data points.

65
Q

What is Holt-Winters method?

A

A time series forecasting technique that accounts for trend and seasonality.

66
Q

What is a rolling window in time series analysis?

A

A method of computing statistics over a sliding window of past observations.

67
Q

What is a lag variable?

A

A past value of a time series used as a predictor for the current value.

68
Q

What is Granger causality?

A

A statistical hypothesis test to determine if one time series can predict another.

69
Q

What is a cointegration test?

A

A test used to determine if two or more time series have a long-term relationship.

70
Q

What is a structural break in time series?

A

A sudden change in the relationship between time series variables.

71
Q

What is seasonality in time series?

A

A repeating pattern of fluctuations over a fixed period.

72
Q

What is a trend in time series?

A

A long-term increase or decrease in data values over time.

73
Q

What is forecasting?

A

The process of predicting future values based on historical data.

74
Q

What is autocorrelation?

A

The correlation of a time series with its past values.

75
Q

What is partial autocorrelation?

A

The correlation of a time series with its past values after removing intermediate dependencies.

76
Q

What is the ACF (Autocorrelation Function)?

A

A function that measures how a time series is correlated with its past values.

77
Q

What is the PACF (Partial Autocorrelation Function)?

A

A function that shows the direct relationship between a time series and its lags.

78
Q

What is white noise in time series?

A

A sequence of random values with a constant mean and variance and no correlation between observations.

79
Q

What is a random walk?

A

A time series model where each step is randomly determined, often used in financial markets.

80
Q

What is a unit root?

A

A characteristic of non-stationary time series where shocks have a permanent effect.

81
Q

What is the Augmented Dickey-Fuller (ADF) test?

A

A statistical test used to determine whether a time series is stationary.

82
Q

What is a time series?

A

A sequence of observations recorded at regular time intervals.

83
Q

What is stationarity in time series?

A

A time series is stationary if its statistical properties (mean, variance) do not change over time.

84
Q

What is the difference between additive and multiplicative seasonality?

A

Additive seasonality means variations are constant over time, while multiplicative means they increase or decrease with the trend.

85
Q

What is differencing in time series?

A

A technique used to remove trends by computing the difference between consecutive observations.

86
Q

What is an autoregressive (AR) model?

A

A model where future values depend on previous values plus noise.

87
Q

What is a moving average (MA) model?

A

A model where future values depend on past forecast errors.

88
Q

What is an ARMA model?

A

A combination of autoregressive (AR) and moving average (MA) models.

89
Q

What is an ARIMA model?

A

A model combining autoregression, differencing, and moving averages for forecasting.

90
Q

What is a seasonal ARIMA (SARIMA) model?

A

An extension of ARIMA that includes seasonal components.

91
Q

What is exponential smoothing?

A

A forecasting technique that applies weighted averages to past data points.

92
Q

What is Holt-Winters method?

A

A time series forecasting technique that accounts for trend and seasonality.

93
Q

What is a rolling window in time series analysis?

A

A method of computing statistics over a sliding window of past observations.

94
Q

What is a lag variable?

A

A past value of a time series used as a predictor for the current value.

95
Q

What is Granger causality?

A

A statistical hypothesis test to determine if one time series can predict another.

96
Q

What is a cointegration test?

A

A test used to determine if two or more time series have a long-term relationship.

97
Q

What is a structural break in time series?

A

A sudden change in the relationship between time series variables.

98
Q

What is seasonality in time series?

A

A repeating pattern of fluctuations over a fixed period.

99
Q

What is a trend in time series?

A

A long-term increase or decrease in data values over time.

100
Q

What is forecasting?

A

The process of predicting future values based on historical data.