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Can you explain the underlying assumptions of linear regression, and the importance of taking them into account when interpreting model outcomes?
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Interview question asked to Data Scientists interviewing at Red Hat, DataRobot, Asana and others: Can you explain the underlying assumptions of linear regression, and the importance of taking them into account when interpreting model outcomes?.