DA0-002 Data Acquisition and Preparation Practice Question
A data analyst needs to sample 1000 customers from a database of 100,000 customers for a survey, ensuring every customer has an equal chance of selection. Which sampling method is most appropriate?
⚠ Common exam trap
DA0-002 often tests the distinction between simple random sampling and stratified or systematic sampling, causing candidates to choose stratified when the requirement is equal chance for all, not representation of subgroups.
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
✓
Simple random sampling
Simple random sampling is the method where every individual in the population has an equal chance of being selected. This directly matches the requirement that every customer has an equal chance of selection. It is the most straightforward probability sampling technique.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Cluster sampling
Why it's wrong here
Cluster sampling selects whole groups, so individual customers within a chosen cluster share selection probability, violating equal chance for every customer. It suits geographically dispersed populations where visiting every area is impractical. Simple random sampling gives each of the 100,000 customers an equal chance.
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Stratified sampling
Why it's wrong here
Stratified sampling divides the population into strata and samples within each, so selection probability varies by stratum rather than being equal for all customers. It suits ensuring representation of subgroups, such as age bands. Simple random sampling gives every customer an equal chance.
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Systematic sampling
Why it's wrong here
Systematic sampling picks every 100th customer after a random start, giving equal chance only when the list has no periodic pattern. A periodic ordering can bias selection. It suits large, randomly ordered lists where simple random sampling is operationally awkward.
- ✓
Simple random sampling
Why this is correct
Simple random sampling assigns every customer an identical selection probability, directly satisfying the equal-chance constraint. By drawing 1000 individuals from the full 100,000-customer frame without stratification or systematic intervals, it avoids selection bias. Stratified, cluster, or convenience methods would alter probabilities across subgroups or rely on non-random access.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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.