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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What are outliers?
💡 Hint: Think about extreme values in data.
Question 2
Easy
Give one method to handle outliers.
💡 Hint: What can we do with data points that are much higher or lower?
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 an outlier?
- A value that is average
- A data point that is significantly different
- A missing value
💡 Hint: Think about what makes a data point unusual.
Question 2
True or False: Removing outliers is always the best method of handling them.
- True
- False
💡 Hint: Consider the implications of losing data.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
A dataset containing house prices shows a few extremely high values due to luxury homes. Discuss how you would address these outliers and justify your approach.
💡 Hint: Consider how the outliers influence the overall predictions.
Question 2
If a linear regression model's results skew due to an outlier, what steps can you take during preprocessing to ensure better outcomes? Provide specific transformation methods you would apply.
💡 Hint: Think about how we rescale data to handle skew.
Challenge and get performance evaluation