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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does data cleaning entail?
💡 Hint: Think about why we need to prepare data.
Question 2
Easy
What is the purpose of handling missing data?
💡 Hint: Consider what missing values can cause.
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 data cleaning ensure?
- Data completeness
- Consistency in data
- All of the above
💡 Hint: Consider the main goals of data cleaning.
Question 2
True or False: Normalization transforms data into a range from 0 to 1.
- True
- False
💡 Hint: Think about how the extremes of the data are affected.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a dataset with significant missing values in multiple columns, outline a strategy to address missing data efficiently while retaining the dataset’s integrity.
💡 Hint: Think about how much missing data is acceptable and how best to preserve data utility.
Question 2
You are modeling income data that has extreme outliers. Describe the steps you would take to handle these outliers before proceeding with the analysis.
💡 Hint: Consider both numerical results and visual assessments.
Challenge and get performance evaluation