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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is data cleaning?
💡 Hint: It involves making sure the data is accurate.
Question 2
Easy
Why are missing values a problem in data analysis?
💡 Hint: Think about what happens if we base decisions on incomplete information.
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 data cleaning?
- Removing duplicates
- Making data accurate
- Both of the above
💡 Hint: Think about all the things you would do to ensure data’s reliability.
Question 2
True or False: Normalization ensures all entries in a dataset are in the same format.
💡 Hint: Consider how this would affect comparing different data points.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a dataset with mixed formats for dates (e.g., MM/DD/YYYY and DD/MM/YYYY), what steps would you take to ensure all date entries are uniform?
💡 Hint: Think about how you would set a standard for all data points.
Question 2
A dataset with 20% missing values across key fields is provided. Discuss the pros and cons of imputation vs. deletion for handling these values.
💡 Hint: Consider what you gain and lose with each approach.
Challenge and get performance evaluation