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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is a likelihood function?
💡 Hint: Think about the relationship between probability and observed data.
Question 2
Easy
Why do we use log-likelihood instead of likelihood?
💡 Hint: Consider how multiplication can be cumbersome with multiple small probabilities.
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 primary goal of maximizing log-likelihood?
- To minimize error
- To maximize data fit
- To calculate likelihood ratios
💡 Hint: Remember the purpose of likelihood in data modeling.
Question 2
True or False: Log-likelihood simplifies products into sums.
- True
- False
💡 Hint: Think how likelihoods are calculated across multiple instances.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a dataset and the likelihood function, explain how you would proceed to maximize log-likelihood. Discuss any potential pitfalls you might encounter.
💡 Hint: Think about calculus and optimization methods you know.
Question 2
Consider a case where you maximized log-likelihood, but your model is overfitting. What remedies would you suggest?
💡 Hint: Reflect on ways to prevent too much detail in your models.
Challenge and get performance evaluation