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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is bootstrapping?
💡 Hint: Think about how we can simulate data sampling.
Question 2
Easy
Why do we use bootstrapping?
💡 Hint: Consider situations with limited data.
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 purpose of bootstrapping?
- To improve dataset size
- To estimate confidence intervals
- To classify data
💡 Hint: Consider what bootstrapping achieves statistically.
Question 2
Bootstrapping uses sampling with replacement. True or False?
- True
- False
💡 Hint: Reflect on our keyword 'replacement'.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are given a dataset with 100 observations. Describe how you would employ bootstrapping to calculate confidence intervals for the mean of a chosen numerical feature.
💡 Hint: Focus on how you derive the mean from the bootstrap samples.
Question 2
Critically discuss how bootstrapping could lead to incorrect conclusions in a model evaluation if the data sample is not representative of the population.
💡 Hint: Consider the implications of having a skewed dataset.
Challenge and get performance evaluation