Practice Stationarity In Time Series (10.3) - Time Series Analysis and Forecasting

Practice: Stationarity in Time Series

Lesson 10.3Time Series Analysis and Forecasting

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10 questions

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4 cards from this section. Quick, good the night before a test.
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Quiz
4 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
Define stationarity in the context of time series analysis.
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Think about whether the series behaves the same throughout.
Question 2.
What is the difference between strict and weak stationarity?
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Consider whether you’re talking about all properties or just some.
3Question 3.
What does it mean when a time series is stationary?
- Its mean and variance change over time.
- Its mean and variance do not change over time.
- It contains a unit root.
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Think about the definition of stationarity.
4Question 4.
True or False: The KPSS test null hypothesis states that a time series is stationary.
- True
- False
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Recall which tests have what hypotheses.
Question 5.
You observe a fluctuating dataset over several years that appears to show trends. How would you apply the ADF and KPSS tests to analyze its properties?
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Focus on the sequential order of testing and transforming.
Question 6.
Given a non-stationary time series data, describe how you would verify and ensure its stationarity prior to analysis.
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Think about layers: check visually first, then statistically.

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