# Representative sample

URL: https://sellmydatatoai.net/glossary/representative-sample

A representative sample is a subset of a dataset drawn so its mix of record types, dates and quality reflects the whole archive, not hand-picked highlights.

A representative sample is a subset of records selected so that it reflects the full dataset in content, date range, quality and format. It lets a buyer judge the whole archive without seeing all of it.

## How should a representative sample be drawn?

A representative sample should be drawn at random across the archive, not hand-picked. Stratified sampling, where records are drawn in proportion from each system, year or record type, makes sure small but valuable segments appear. Label the sample with how it was drawn.

## Why do buyers distrust samples?

Buyers distrust samples because a seller can show the best records and deliver the rest. Contributors to a 2026 Hugging Face forum thread on selling datasets described this as a trust deadlock and suggested labeled stratified samples, paid pilots, acceptance tests and staged payments to break it.

A representative sample is one of the eight points in our [seller vetting standard](https://sellmydatatoai.net/how-we-vet). See [how to evaluate a dataset sample](https://sellmydatatoai.net/guides/how-to-evaluate-dataset-samples) and [hold-out set](https://sellmydatatoai.net/glossary/hold-out-set).