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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the formula for calculating the Z-score?
💡 Hint: Remember to consider how both mean and standard deviation are involved.
Question 2
Easy
Why is standardization important?
💡 Hint: Think about different scales of 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 standardization do to a dataset?
- Convert all data to a common scale
- Remove outliers
- Change categorical data to numerical
💡 Hint: Think about the concept of mean and deviation.
Question 2
True or False: Standardization is necessary for all types of data.
- True
- False
💡 Hint: Consider cases where features are homogeneous.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Suppose you have a dataset with weight, height, and age of individuals. Explain how you would prepare this dataset for a clustering algorithm using Z-score scaling.
💡 Hint: Consider how different measurements affect clustering.
Question 2
You are given a choice between normalization and standardization for a dataset heavily skewed by outliers. Which method would you choose and why?
💡 Hint: Recall the effect of outliers on each method.
Challenge and get performance evaluation