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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define causal discovery in your own words.
💡 Hint: Think about the difference between correlation and causation.
Question 2
Easy
What does the PC algorithm stand for?
💡 Hint: What type of algorithm is this?
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 goal of causal discovery?
- To identify correlations
- To determine causal relationships
- To classify data
💡 Hint: Remember the difference between correlation and causation.
Question 2
True or False: Score-based methods do not rely on measuring independence.
- True
- False
💡 Hint: Consider what each method relies on for causal discovery.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You have data from two cities regarding air pollution levels and respiratory illness rates. Describe how you might use PC and GES differently to analyze the data for causal relationships.
💡 Hint: Consider the strengths of each method.
Question 2
Design a mini-research study attempting to use LiNGAM for causal discovery in social sciences, outlining the assumptions you need to verify.
💡 Hint: Reflect on the assumptions necessary for model validity.
Challenge and get performance evaluation