Practice Causal Graphs and DAGs - 10.1.2 | 10. Causality & Domain Adaptation | Advance Machine Learning
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does DAG stand for?

πŸ’‘ Hint: Think about the direction and cycles in graphical representations.

Question 2

Easy

What do nodes represent in a DAG?

πŸ’‘ Hint: Consider what components make up a graph.

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 a directed edge in a DAG indicate?

  • Causation
  • Correlation
  • Independence

πŸ’‘ Hint: Think about the directionality that gives it meaning.

Question 2

Is d-separation used to establish conditional independence?

  • True
  • False

πŸ’‘ Hint: Remember the connection between d-separation and independence.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Create a DAG that illustrates the relationship between education level, job opportunities, and income. Discuss the causal pathways.

πŸ’‘ Hint: Consider how changes in the education level might flow through job opportunities to affect income.

Question 2

Evaluate the impact of controlling for a third variable in a potential confounding scenario using a DAG. What happens to the observed relationships?

πŸ’‘ Hint: Identify which variable serves to obscure true relationships in the absence of control.

Challenge and get performance evaluation