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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is data cleaning?
💡 Hint: Think about why accuracy in data is important.
Question 2
Easy
Name one reason why standardization is important.
💡 Hint: Consider the formats of the 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 does data cleaning involve?
- Correcting errors
- Adding new data
- Removing duplicates
💡 Hint: It's the opposite of introducing data.
Question 2
True or False: Standardization ensures that all data points are on the same scale.
- True
- False
💡 Hint: Consistency is key in data analysis.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You inherit a dataset with 20% missing values across various columns. Discuss a comprehensive strategy for addressing these missing values, including potential biases in your approach.
💡 Hint: Categorize missingness and determine an ideal approach of filling in or removing.
Question 2
You notice that categorical data in your dataset is inconsistent (e.g., 'male' vs 'Male' vs 'M'). Create a step-by-step guide for standardizing this entry.
💡 Hint: Consider the majority format selection or how the analysis might impact result comprehensibility.
Challenge and get performance evaluation