Practice Measurement Bias (Feature Definition Bias / Proxy Bias) - 1.1.3 | Module 7: Advanced ML Topics & Ethical Considerations (Weeks 14) | Machine Learning
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1.1.3 - Measurement Bias (Feature Definition Bias / Proxy Bias)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Define Measurement Bias in your own words.

πŸ’‘ Hint: Think about how biases can emerge during model training.

Question 2

Easy

What is a Proxy Bias?

πŸ’‘ Hint: Consider how indirect measures might mask real discrepancies.

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 Measurement Bias?

πŸ’‘ Hint: Think about how different definitions can alter data representations.

Question 2

True or False: Proxy Bias can occur even if sensitive variables are not included in the model.

  • True
  • False

πŸ’‘ Hint: Consider how indirect associations can still influence outcomes.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a dataset that measures customer satisfaction based solely on online surveys, outline a plan to address possible Measurement Bias.

πŸ’‘ Hint: Think about incorporating multiple perspectives to gather balanced data.

Question 2

Critically evaluate the implications of using proxy variables in AI models. How can they lead to unintended discrimination?

πŸ’‘ Hint: Consider how proxies might oversimplify complex social issues.

Challenge and get performance evaluation