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DA0-002 Data Acquisition and Preparation Practice Question

A data analyst needs to sample 10% of customers from each of three regions (North, South, Central) to ensure proportional representation. Which sampling method should be used?

⚠ Common exam trap

The trap is confusing stratified sampling with cluster sampling; candidates might think that sampling from each region is cluster sampling, but cluster sampling involves selecting entire groups, not sampling within each group.

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 involves dividing the population into homogeneous subgroups (strata) based on a characteristic (here, region) and then sampling proportionally from each stratum. This ensures that each region is represented in the sample according to its proportion in the population. Simple random sampling does not guarantee proportional representation.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • ✗

    Systematic sampling

    Why it's wrong here

    Systematic sampling selects every kth element from a single ordered list, which does not enforce a fixed 10% per region unless each region is sampled separately. It is tempting for its simplicity on large ordered datasets, and would be correct when a sampling interval across one homogeneous frame suffices.

  • ✗

    Cluster sampling

    Why it's wrong here

    Cluster sampling selects whole groups and surveys all members within chosen clusters, so it does not guarantee a 10% draw from every region. It is tempting when geographically dispersed populations make individual selection costly, and would be correct if entire regions were randomly chosen as sampling units.

  • ✓

    Stratified sampling

    Why this is correct

    Stratified sampling divides the population into the three region strata, then draws a 10% sample independently within each. This guarantees proportional representation of North, South and Central, satisfying the stem's requirement that each region contributes its correct share rather than leaving representation to chance.

  • ✗

    Simple random sampling

    Why it's wrong here

    Simple random sampling draws from the entire population, so each region's 10% share is not guaranteed and small regions may be under-represented. It is tempting because it is the baseline unbiased method, and it would be correct when the population is homogeneous and no subgroup proportionality is required.

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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

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