PracHub
QuestionsPremiumCoachesLearningGuidesInterview Prep
|Home/Machine Learning/Bnp

What are linear regression assumptions?

Last updated: Mar 29, 2026

Quick Overview

Assesses understanding of the assumptions underlying ordinary least squares linear regression and the application of diagnostic methods to ensure unbiased parameter estimates and valid statistical inference.

  • easy
  • Bnp
  • Machine Learning
  • Data Scientist

What are linear regression assumptions?

Company: Bnp

Role: Data Scientist

Category: Machine Learning

Difficulty: easy

Interview Round: Technical Screen

You fit an ordinary least squares (OLS) linear regression model. 1) What are the key assumptions behind OLS (for unbiasedness and for valid inference)? 2) How would you diagnose common violations? 3) What are typical mitigations if assumptions fail?

Quick Answer: Assesses understanding of the assumptions underlying ordinary least squares linear regression and the application of diagnostic methods to ensure unbiased parameter estimates and valid statistical inference.

Bnp logo
Bnp
Jan 5, 2026, 12:00 AM
Data Scientist
Technical Screen
Machine Learning
2
0

You fit an ordinary least squares (OLS) linear regression model.

  1. What are the key assumptions behind OLS (for unbiasedness and for valid inference)?
  2. How would you diagnose common violations?
  3. What are typical mitigations if assumptions fail?

Solution

Show

Submit Your Answer

Sign in to leave a comment

Loading comments...

Browse More Questions

More Machine Learning•More Bnp•More Data Scientist•Bnp Data Scientist•Bnp Machine Learning•Data Scientist Machine Learning
PracHub

Master your tech interviews with 8,500+ real questions from top companies.

Product

  • Questions
  • Learning Tracks
  • Interview Guides
  • Resources
  • Premium
  • For Universities
  • Student Access

Browse

  • By Company
  • By Role
  • By Category
  • Topic Hubs
  • SQL Questions
  • Compare Platforms
  • Discord Community

Support

  • support@prachub.com
  • (916) 541-4762

Legal

  • Privacy Policy
  • Terms of Service
  • About Us

© 2026 PracHub. All rights reserved.