Sample size counts the observations available for estimating performance or testing a claim. More independent observations usually reduce uncertainty, although data quality and representativeness remain as important as the raw count.
A very small sample can produce an impressive result through luck. This is especially important when outcomes vary widely or when several observations are connected to the same market conditions.
A credible evaluation reports the sample definition, time period, missing data and uncertainty. It should not treat a few favorable days as proof that a model or strategy will keep working.
ELI5
Sample size is how many separate examples or results you have looked at. A tiny sample can give a misleading picture because chance has a large influence.
For example, five good or mixed trading days cannot show how a strategy behaves across many kinds of market conditions. More independent results give a stronger basis for judgment.
