DA0-002 Data Analysis Practice Question
A data analyst wants to segment customers based on purchasing behavior such as frequency, monetary value, and recency. Which TWO clustering evaluation methods can help determine the optimal number of clusters? (Select two.)
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
✓
Silhouette score
The elbow method uses within-cluster sum of squares, and the silhouette score measures cohesion and separation. Both help choose k. Correlation coefficient is for association, not clustering. ANOVA and t-test are for hypothesis testing.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Correlation coefficient
Why it's wrong here
Measures linear relationship, not cluster quality.
- ✗
ANOVA
Why it's wrong here
Compares means among groups, not for clustering.
- ✓
Silhouette score
Why this is correct
Measures how similar an object is to its own cluster vs others.
- ✗
t-test
Why it's wrong here
Compares two means, not clustering evaluation.
- ✓
Elbow method
Why this is correct
Plots WCSS vs k to find elbow.
Go deeper
Related to this question
About these practice questions
Courseiva writes every DA0-002 question from scratch — 986 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DA0-002 practice question is part of Courseiva's free CompTIA 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 DA0-002 exam.