Definition
Sample size is the number of observations (hands, trials, or simulations) used to estimate an underlying probability or winrate.
Sample size
The amount of data needed to reduce noise and estimate true outcomes.
Key points
- Monte Carlo equity estimates improve with more samples.
- Poker results need large samples to overcome variance.
- Confidence intervals shrink as sample size grows.
Common misconceptions
Myth
A few sessions prove I’m a winner.
Reality
Short samples are dominated by variance.
Myth
More samples always means exact.
Reality
More samples reduces noise but doesn’t fix wrong range assumptions.