- Last Updated: - [[2021-01-26]] - [[2020-12-28]] - In [[Load Testing]], we should take the extra step of considering whether the results we gained from our load tests is truly representative of what we'd get in production. - In [[Data science]], this involves awareness of the distinction between __empirical or sample data__ collected and population data. - Was it a [[Production-like environment]]? - "Is it a large enough sample?" - "Was it collected in a way that it could accurately describe the target population?" - "Was the sample random?"