DA0-002 Data Acquisition and Preparation Practice Question
A data analyst wants to randomly select 100 customers from a database for a survey, ensuring that the sample reflects the proportion of male and female customers in the population. Which sampling method is most appropriate?
⚠ Common exam trap
Test-takers frequently confuse stratified sampling with cluster sampling — both involve grouping, but stratification samples within every group to ensure representation, while clustering samples entire groups and ignores proportional representation.
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
✓
Stratified sampling
Stratified sampling divides the population into homogeneous subgroups (strata) — here, male and female — and then draws random samples from each stratum in proportion to its size in the population. This guarantees the sample mirrors the population's gender proportions, which is exactly what the analyst requires. Simple random sampling could, by chance, under- or over-represent one gender.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Stratified sampling
Why this is correct
Stratified sampling divides the population into strata (male and female) then samples proportionally within each, guaranteeing the sample mirrors the population's gender proportions. Simple random sampling could skew those proportions by chance, failing the stem's proportionality constraint.
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Cluster sampling
Why it's wrong here
Cluster sampling divides the population into groups and samples whole clusters, so it cannot guarantee the male/female proportions the survey requires. It is tempting because it cuts fieldwork cost when a full sampling frame is unavailable, and would suit geographically dispersed populations where random cluster selection is practical.
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Simple random sampling
Why it's wrong here
Simple random sampling gives every customer an equal chance of selection, but it does not enforce the population's male/female proportions, so the sample may misrepresent them. It is tempting because it is the default unbiased method, and would be correct when no subgroup proportionality is required.
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Systematic sampling
Why it's wrong here
Systematic sampling picks every nth record from an ordered list, so it does not enforce the male/female proportions present in the population. It is tempting because it is a probability method, but it would be correct only when the list order is unrelated to the stratifying variable.
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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.