Key Assumptions Underlying Linear Regression

Requirements Clarification & Assessment

To effectively answer the interview question, it is essential to clarify and assess the requirements:

1. Understanding of Linear Regression:

   • The candidate should demonstrate a solid understanding of linear regression as a statistical method used for modeling the relationship between a dependent variable and one or more independent variables.

2. Knowledge of Assumptions:

   • The candidate must explain the assumptions underlying linear regression models, including their significance and implications.

3. Explanation of Assumptions:

   • The candidate should be able to explain each assumption clearly, using examples or analogies to illustrate their points.

4. Implications of Assumption Violations:

   • Discuss what happens when these assumptions are violated and how it impacts the model's performance and reliability.

5. Practical Considerations:

   • Discuss methods or techniques to diagnose and address assumption violations in real-world scenarios.