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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define stationarity in the context of time series analysis.
💡 Hint: Think about whether the series behaves the same throughout.
Question 2
Easy
What is the difference between strict and weak stationarity?
💡 Hint: Consider whether you’re talking about all properties or just some.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
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.
💡 Hint: Think about the definition of stationarity.
Question 2
True or False: The KPSS test null hypothesis states that a time series is stationary.
- True
- False
💡 Hint: Recall which tests have what hypotheses.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
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?
💡 Hint: Focus on the sequential order of testing and transforming.
Question 2
Given a non-stationary time series data, describe how you would verify and ensure its stationarity prior to analysis.
💡 Hint: Think about layers: check visually first, then statistically.
Challenge and get performance evaluation