Why sample size changes what a result means
Launch library · evergreen read
A result drawn from a handful of people tells you much less than the same result drawn from thousands, even if the headline figure looks identical on the page. Small samples are far more likely to reflect chance or unusual circumstance rather than any pattern that would hold more broadly across a wider population.
Sample size interacts with how the sample was chosen, since a small but carefully selected group can sometimes be more informative than a large but poorly chosen one. Both size and selection method need to be considered together before treating a result as reliable enough to build a claim on.
When a claim relies on a very small sample, treating it as suggestive rather than conclusive is the more honest approach. Flagging that limitation openly, rather than hiding it, tends to build more lasting trust than presenting an uncertain result as settled fact to a sceptical audience.