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  1. M&E Library/
  2. Topics/
  3. Sampling
Topic Hub

Sampling

How many people to survey, how to select them, and how to avoid the mistakes that invalidate your data. Sample size calculation, sampling methods, design effect, and practical guidance.

Sampling Calculator
Calculate the sample size you need for surveys, evaluations, and monitoring activities
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How Do I Choose?· 4

Side-by-side comparisons, decision trees, and practical guidance for common M&E decisions.

How Do I Choose?

Side-by-side comparisons, decision trees, and practical guidance for common M&E decisions.

Common Sampling Mistakes in M&E
The eight sampling mistakes that undermine M&E data quality: wrong frames, ignored design effect, field substitution errors, and analysis overclaims.
How to Choose
How to Choose Sample Size for M&E
A practical guide to sample size for program evaluations, with rules of thumb, worked examples, and budget-statistics tradeoffs.
How to Choose
Probability vs Non-Probability Sampling: When to Use Each
Probability vs non-probability sampling in M&E: when each approach is valid, which method fits your context, and five common mistakes that invalidate findings.
Comparison
Cluster Sampling vs Stratified Sampling
Cluster sampling saves money when populations are spread out. Stratified sampling ensures subgroup comparisons. When to use each.
Comparison

Reference Library· 7

Overviews (3)

Baseline Design
A structured approach to collecting initial condition data that directly informs project decisions, minimizes burden, and enables valid comparison with endline measurements.
Disaggregation
The breakdown of aggregate data by sub-group characteristics, such as sex, age, location, or vulnerability status, to reveal inequities and differences in program reach and outcomes.
Sampling Methods
Systematic approaches for selecting a subset of a population to represent the whole, balancing statistical validity with practical constraints.

Quick Reference (4)

Census vs Sample: When to Use Each in M&ECluster SamplingPurposive SamplingRandom Sampling

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