Linear, Multiple Regression Interview Questions Set 3

This page lists down the practice tests / interview questions 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 linear regression models:

  • Hypothesis testing (Null hypothesis) vis-a-vis P-value
  • T-tests vis-a-vis ANOVA (Analysis of Variance) F-tests
  • R-squared vs adjusted R-Squared

Note some of the following in relation with tests:

  • Linear association between dependent and independent variables is determined using both T-test and ANOVA F-tests
  • Adjusted R-Squared value is used to determine the impact of introducing new independent variable in the regression model. As like R-squared value which increases with addition of new predictor variables, adjusted R-squared value increased only when there is a positive impact or else the value of adjusted R-squared value decreases.

Other tests in this series includes some of the following:

[wp_quiz id=”5775″]

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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