Probability Proportional to Size Sampling (PPS) is a widely used method in survey research and statistics. It ensures that populations of different sizes are fairly represented, giving larger clusters a higher chance of selection while keeping the overall probability equal for each household or unit.
This technique, first introduced by Hansen and Hurwitz (1943), is the foundation for many large-scale national surveys, demographic studies, and health or education research projects. To make this method easy to understand, we’ve prepared a complete guide in PDF format that explains:
- What PPS sampling is and why it’s important
- How to calculate probabilities in multi-stage sampling
- Examples using real population data (Andhra Pradesh, India)
- Cumulative Total Method vs. Lahiri’s Method
- Rural vs. Urban representation in survey samples
Download the Probability Proportional to Size Sampling
This PDF explains step-by-step how PPS sampling works, with diagrams, formulas, and examples.
Why Probability Proportional to Size Sampling Matters
PPS Sampling is considered one of the fairest and most efficient sampling methods because:
- It ensures equal probability of selection for every household, regardless of cluster size.
- It reduces bias and simplifies survey analysis.
- It creates a self-weighting design — no complicated weighting adjustments needed later.
This is why PPS sampling is used in surveys like NFHS, DHS, and NSSO.
👉 For background reading, see UNICEF’s MICS methodology and World Bank survey sampling guidelines.
Who Should Use PPS Sampling?
PPS Sampling is essential for:
- Researchers designing large-scale surveys
- Students studying statistics or survey methodology
- Government agencies conducting population or health studies
- NGOs measuring impact through representative surveys
If you are exploring other sampling techniques, check out our complete sampling methods overview for comparisons.
Conclusion
If you are a student, researcher, or policymaker working with survey design, Probability Proportional to Size Sampling is a method you should know.