I am taking a stats course right now and we're studying the bootstrap. One lecture slide says:
"These methods for creating a confidence interval only work if the bootstrap distribution is smooth and symmetric"
If the bootstrap distribution is highly skewed or looks “spiky” with gaps, you will need to go beyond intro stat to create a confidence interval
I didn't get an explanation on why this is so. Why do we need a smooth and symmetric bootstrap?
We're simply bootstrapping the mean statistic. We compute N bootstrap datasets from the given sample dataset then compute the mean of each bootstrap dataset and visualize the resulting distribution. That is when I was told the above.