Which of the following is NOT a common assumption of linear regression? A) Multicollinearity B) Normality of residuals C) Independence of residuals D) Linearity

Understand the Problem

The question is asking which option listed is not a common assumption of linear regression. This involves understanding the standard assumptions related to linear regression models.

More Information

Linear regression assumes linearity, independence, normality, and homoscedasticity, while multicollinearity is a condition that can affect the model but is not an assumption itself.

Tips

A common mistake is to confuse conditions affecting model performance, like multicollinearity, with assumptions that need to be met.

Sources

• 6 Assumptions of Linear Regression - Analytics Vidhya - analyticsvidhya.com
• Understanding the Assumptions of Linear Regression Analysis - statisticssolutions.com
• The Four Assumptions of Linear Regression - Statology - statology.org