Practice Conditional Independence (4.3.1) - Graphical Models & Probabilistic Inference
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Conditional Independence

Practice - Conditional Independence

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does conditional independence mean?

💡 Hint: Think about how knowledge of C could influence A and B.

Question 2 Easy

Explain how conditional independence relates to Bayesian networks.

💡 Hint: Think about how knowing one variable can make others irrelevant.

1 more question available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does A ⊥ B | C signify?

A and B are dependent
A and B are independent given C
C is unrelated to A and B

💡 Hint: Focus on the meaning of conditional independence.

Question 2

True or False: d-Separation can help identify conditional independence in Bayesian networks.

True
False

💡 Hint: Recall what d-Separation checks in graphical models.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

In a network of symptoms and diseases, if Disease A causes Symptom X and Symptom Y, how would you determine if Symptom X and Symptom Y are conditionally independent given Disease A?

💡 Hint: Consider the chain of causation.

Challenge 2 Hard

Construct a scenario with three random variables where two of them are conditionally independent given a third. Illustrate this with a diagram.

💡 Hint: Visualize the relationships clearly to spot dependencies.

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Reference links

Supplementary resources to enhance your learning experience.