When doing a bootstrap, if we use a sample size that is too small, how does this bias our results?

Question

Quizplus · Accepted Answer

Using a sample size that is too small in bootstrap can lead to underestimation of the variability in the data, resulting in confidence intervals that are too narrow and standard errors that are too small. This is because a small sample size does not capture the full variability of the population, leading to overly optimistic (narrow) estimates of confidence intervals and smaller standard errors than if a larger, more representative sample were used.

When Doing a Bootstrap, If We Use a Sample Size