1
Simple random sampling draws 400 customer IDs from a complete annual customer list with a reproducible random seed.
8 Probability Sampling Examples
Use these examples to study structure, specificity, tone, and variation. They are demonstrations—not claims about a real person or organization unless the example itself makes that explicit.
Before you copy
What to notice in the examples
A strong probability-sampling plan defines the frame, randomization procedure, selection probabilities, strata or clusters when used, and any weighting needed to recover population estimates.
- Complete or defensible sampling frame.
- Random selection rule with known probabilities.
- Stratification, clustering, or stages where relevant.
- Weighting and nonresponse treatment for analysis.
2
Stratified sampling draws students separately from first, second, third, and fourth years to ensure each year is represented.
3
Systematic sampling selects every 25th record after a random starting position in an ordered list.
4
Cluster sampling randomly selects schools, then surveys all eligible teachers within selected schools.
5
Multistage sampling selects districts, then villages, then households within villages.
6
A workforce survey oversamples a small department and later weights responses by inverse selection probability.
7
A household survey uses probability-proportional-to-size selection for areas before selecting homes within each area.
8
An archive study randomly selects 12 issues from each publication year to balance temporal coverage.
Keep the underlying decision or pattern, then replace the subject, evidence, relationship, constraints, and tone with details that belong to your situation. If your final line still works after swapping only one noun, it may be too close to the example.