Linear, Multiple Regression Interview Questions Set 2

This page lists down the practice tests / interview questions and answers for Linear (Univariate / Simple Linear) / Multiple (Multilinear / Multivariate) regression in machine learning. Those wanting to test their machine learning knowledge in relation with linear/multi-linear regression would find the test useful enough. The goal for these practice tests is to help you check your knowledge in numeric regression machine learning models from time-to-time. More importantly, when you are preparing for interviews, these practice tests are intended to be handy enough. Those going for freshers / intern interviews in the area of machine learning would also find these practice tests / interview questions to be very helpful.

This test primarily focus on following two concepts related with evaluation of linear regression models:

  • Coefficient of determination (R-squared)
  • Pearson correlation coefficient

Note that the above two concepts are used to understand some of the following:

  • Impact of one or more parameters on the dependent variable in positive or negative manner
  • Overall impact/performance of regression model based on addition of one or more independent variables

Other tests in the series includes some of the following:

[wp_quiz id=”5774″]

In case you have not scored good enough, it may be good idea to go through basic machine learning concepts in relation with linear / multi-linear regression. Following is the list of some good courses / pages:


Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking.

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