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Regression Analysis Skills Test
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Entry Level/Mid/Senior

Regression Analysis ML Skills Test

This skill test helps recruiters and hiring managers evaluate top individuals efficiently. Regression analysis is essential in various ML roles, including Machine Learning Scientists and Data Analysts.  Scale your hiring and upskilling by reducing technical screening time by 80%.

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What is Regression Analysis?

It helps you understand the relationship between two or more variables in machine learning. This statistical method uses various metrics to predict continuous outcomes of the dependent variable(s) based on the value of the predictable variable(s). Widely used for forecasting, it can help organizations find trends in data like real estate prices, stock prices, map salary changes, etc.

Why Use iMocha's Regression Analysis Skills Test?

This Skills Test is created by a subject matter expert (SME) to assess candidates and employees on multiple concepts of regression, predictive modeling, reasoning, analytical thinking, etc. This customizable test can help talent managers test individuals’ aptitude, knowledge, and experience in the field. As a result, you can assess efficiently and make data-driven decisions.

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How it works

Test Summary

Through this assessment, you can assess capabilities like:

  • Fundamentals like sci-kit-learn, TensorFlow, PyTorch, outliers, and overfitting or underfitting.
  • Types of regression like logistic, linear, support vector, polynomial, etc.
  • Analytical and critical thinking skills to draw conclusions using statistical and machine-learning methods.
  • Model selection and evaluation skills like squared error, R-squared, and root mean squared error.
  • Mathematical aptitude and understanding of how equations and other concepts.
  • Technical proficiency in general-purpose and statistical programming languages like R or Python.

Discover the perfect fit for your team! Explore our compelling Machine Learning Engineer job description and attract top talent today!

Useful for hiring
  • Machine Learning Scientist
  • Machine Learning Engineer
  • Data Scientist with AI/ML
  • Data Science Analyst
Test Duration
No. of Questions
Level of Expertise
Entry Level/Mid/Senior
Topics Covered





Sample Question
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You can customize this test by

Setting the difficulty level of the test

Choose easy, medium, or tricky questions from our skill libraries to assess candidates of different experience levels.

Combining multiple skills into one test

Add multiple skills in a single test to create an effective assessment and assess multiple skills together.

Adding your own
questions to the test

Add, edit, or bulk upload your coding, MCQ, and whiteboard questions.

Requesting a tailor-made test

Receive a tailored assessment created by our subject matter experts to ensure adequate screening.
How is this skill test customized?
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iMocha can customize the test based on the competencies the role requires. For example, the test can be customized if you need the candidate to be highly proficient in Python. The test can be customized to assess a candidate's technical skills, like statistical knowledge, hyperparameter tuning, model evaluation, etc. It can also have varying difficulty levels and durations, include more practical than theoretical questions, and be tailored to organizational policies.

What are the most common interview questions related to regression analysis?
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Here are some of the frequently asked interview questions related to this role are:

  • What are linear and non-linear regression?
  • What is multicollinearity?
  • What are MSE and RMSE?
  • What are the real-world applications of regression analysis in ML?
  • What are the basic assumptions of linear regression?

Want to expand your repertoire of interview questions? Please read our latest blog on Machine learning interview questions.

What are the required skill sets to work on regression analysis?
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Here is list of technical and non-technical skills required for this field:


  • Knowledge of Python
  • Model selection
  • TensorFlow
  • PyTorch


  • Problem-solving
  • Communication
  • Attention to detail
  • Analytical Skills