MLS-C01 Exploratory Data Analysis Practice Question
Which THREE techniques are commonly used to detect multicollinearity in a dataset during exploratory data analysis?
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
✓
Eigenvalue analysis from PCA
Options B, C, and D are correct. B: Eigenvalue analysis from PCA can detect multicollinearity; if some eigenvalues are near zero, it indicates high multicollinearity. C: Correlation matrix shows pairwise correlations between features; high correlation coefficients (e.g., >0.8) indicate collinearity. D: Variance Inflation Factor (VIF) quantifies how much a feature's variance is inflated due to multicollinearity; VIF >10 is often considered problematic. Option A is incorrect because a heatmap of missing values visualizes missing data, not relationships between features. Option E is incorrect because a scatter matrix shows pairwise scatter plots, which can reveal linear relationships but is not a quantitative measure for 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.
- ✗
Heatmap of missing values
Why it's wrong here
Missing value heatmap is unrelated to multicollinearity.
- ✓
Eigenvalue analysis from PCA
Why this is correct
Near-zero eigenvalues indicate linear dependencies.
- ✓
Correlation matrix
Why this is correct
High pairwise correlations indicate collinearity.
- ✓
Variance Inflation Factor (VIF)
Why this is correct
VIF > 10 indicates high multicollinearity.
- ✗
Scatter matrix of all features
Why it's wrong here
Scatter matrix shows pairwise plots but no quantitative measure.
Go deeper
Related to this question
About these practice questions
One of 1,672 original MLS-C01 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services 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 MLS-C01 exam.