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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does identifiability mean in causal analysis?
💡 Hint: Think about how true causes can be distinguished from mere correlations.
Question 2
Easy
Why is labeled data important?
💡 Hint: Consider what a model needs to understand to make predictions.
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 the main challenge relating to causal structure in data analysis?
- Identifiability
- Irreversibility
- Correlation
💡 Hint: Recall what’s necessary to understand the ‘why’ behind data.
Question 2
True or False: Domain generalization allows models to work well on unseen data.
- True
- False
💡 Hint: Think about the adaptability of models.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a hypothetical experiment to test for the identifiability of a causal relationship in a set of data suspected to have confounding variables.
💡 Hint: Recall how RCTs allow for isolating effects.
Question 2
Propose a method to deal with limited labeled data in a target domain, explaining its advantages.
💡 Hint: Think about knowledge transfer between different subjects.
Challenge and get performance evaluation