MLS-C01 Exploratory Data Analysis Practice Question
Which THREE techniques are commonly used in exploratory data analysis to understand the relationships between features and the target variable? (Select THREE.)
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
✓
Use box plots to compare feature distributions across target classes.
Options A, C, and D are correct. Box plots (A) are useful for comparing feature distributions across different target classes, revealing differences that may indicate predictive power. Scatter plots or pair plots (D) allow visual inspection of relationships between features and the target, highlighting patterns, clusters, or outliers. A correlation matrix (C) quantifies linear relationships between features and the target variable, helping identify strongly correlated features. B is incorrect because K-means clustering is an unsupervised technique used for grouping data, not for understanding feature-target relationships. E is incorrect because PCA is a dimensionality reduction technique, not a direct method for analyzing relationships between features and a target variable.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use box plots to compare feature distributions across target classes.
Why this is correct
Box plots by class reveal differences in feature distributions.
- ✗
Perform K-means clustering on the features.
Why it's wrong here
Clustering groups data, not for feature-target relationship.
- ✓
Compute the correlation matrix between features and target.
Why this is correct
Correlation measures linear relationship strength.
- ✓
Generate scatter plots or pair plots to visualize feature interactions.
Why this is correct
Pair plots show pairwise relationships including with target.
- ✗
Apply Principal Component Analysis (PCA) to reduce dimensions.
Why it's wrong here
PCA is not primarily for understanding feature-target relationships.
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.