Practice Normalization and Standardization - 2.3.1 | 2. Data Wrangling and Feature Engineering | Data Science Advance
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Normalization and Standardization

2.3.1 - Normalization and Standardization

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the goal of normalization in data processing?

💡 Hint: Think about how this affects feature scales.

Question 2 Easy

What does standardization do to a dataset?

💡 Hint: Recall the transformations that happen during standardization.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main purpose of normalization?

To achieve a mean of zero
To rescale values to a certain range
To reduce data dimensionality

💡 Hint: Think about the range and scaling.

Question 2

Standardization transforms data to have a mean of zero and a standard deviation of 1.

True
False

💡 Hint: Recall the definition of standardization.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Consider the dataset: [10, 20, 30, 40, 50]. Normalize it using Min-Max scaling. What are the results?

💡 Hint: Use the formula: (value - min) / (max - min).

Challenge 2 Hard

Given the dataset with mean 200 and standard deviation 50, standardize the value 300. Explain the significance of standardizing this value.

💡 Hint: What does the resulting z-score signify in terms of data distribution?

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