FAQ: Data Types and Quality - Working with Missing Data

This community-built FAQ covers the “Working with Missing Data” exercise from the lesson “Data Types and Quality”.

Paths and Courses
This exercise can be found in the following Codecademy content:

Machine Learning and AI Fundamentals
Business Intelligence Data Analyst
Data Science Foundations
Data Science Foundations
Data Scientist: Inference Specialist
Data Scientist: Natural Language Processing Specialist
Data Scientist: Analytics Specialist
Data Science Foundations
Data Scientist: Machine Learning Specialist

Principles of Data Literacy

FAQs on the exercise Working with Missing Data

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I am practicing concepts involving Working with Missing Data. One of the questions asks what type of missing data it is. :

The correct answer is Missing At Random, but to me I look at this table and see no real reason the data is missing other than it wasn’t entered properly which would make it MCAR. I can’t predict that the missing values are missing based on the value of another variable which would be MAR (i.e. weight recorded based on gender or age).

Can someone explain why this is Missing At Random (MAR) and not Missing Completely At Random (MCAR)? Or is the correct answer actually MCAR and there is a mistake?