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

Test your understanding with targeted questions related to the topic.

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.

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 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.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

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).

Question 2

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?

Challenge and get performance evaluation