AI Associate Data for AI Practice Question
A data scientist is using Einstein Discovery to analyze sales data. The model results show a high correlation between two predictor variables. Which TWO actions should the data scientist take?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Combine them into a single feature.
Removing one correlated variable or combining them reduces multicollinearity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Apply regularization.
Why it's wrong here
Regularization helps with overfitting but is not specific to pair correlation.
- ✓
Combine them into a single feature.
Why this is correct
Creates a new variable that captures the combined effect.
- ✗
Include both to capture more information.
Why it's wrong here
High correlation can lead to unstable coefficient estimates.
- ✗
Increase the sample size.
Why it's wrong here
More data does not fix multicollinearity.
- ✓
Remove one of the correlated variables.
Why this is correct
Eliminates the correlation entirely.
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This AI Associate practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI Associate exam.