Explain Linear Regression to Non-Technical Stakeholders

Q: Explain Linear Regression to Non-Technical Stakeholders

This question evaluates the ability to explain core supervised learning concepts—specifically linear regression—to non-technical stakeholders and to reason about robustness and evaluation when working with highly imbalanced datasets, measuring both communication skills and technical judgment in the Machine Learning/Data Science domain.

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Question

Scenario

You are explaining core machine learning concepts to non-technical stakeholders during a project discussion.

Questions

Explain linear regression to someone with no data background. Use plain language and a practical example. State the key assumptions and common pitfalls.
When the dataset is highly imbalanced:
- What techniques would you use to build a robust model?
- Why those techniques? Touch on resampling, algorithm-level options, decision thresholds, and evaluation.

Explain Linear Regression to Non-Technical Stakeholders

Scenario

Questions

Solution

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