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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define missing data in time series analysis.
💡 Hint: Think about data points that are not recorded.
Question 2
Easy
What is an outlier?
💡 Hint: Consider extreme values that stand apart.
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 is a common issue caused by missing data?
- Inaccurate predictions
- Increased data volume
- Enhanced reliability
💡 Hint: Consider how absence affects prediction ability.
Question 2
True or False: Outliers should always be removed from a dataset to improve model accuracy.
- True
- False
💡 Hint: Think about the nature of outliers.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are working with a sales forecasting model, and you notice that every December, sales spike unusually due to holiday trends. How would you handle these spikes when defining outliers?
💡 Hint: Consider seasonality patterns and regular trends.
Question 2
A company observes that customer behavior is changing significantly over the years, reflected in their purchase patterns. How could they identify and address concept drift in their forecasting models?
💡 Hint: Think about continuous validation and adaptation.
Challenge and get performance evaluation