Chapter 2 about the stratified sampling example

In chapter 2, there is a stratified sampling:
For example, the US population is composed of 51.3% female and 48.7% male, so a well-conducted survey in the US would
try to maintain this ratio in the sample: 513 female and 487 male. This is called stratified sampling: the population is divided into homogeneous subgroups called strata, and the right number of instances is sampled from each stratum to guarantee that the
test set is representative of the overall population. If they used purely random sampling, there would be about **12%** chance of sampling a skewed test set with either less than **49%** female or more than **54%** female. Either way, the survey results would be significantly biased.

The question is: could you give some explanation how these 12%, 49%, 54% calculated? thanks

Start with the Chapter 2 stratified-sampling passage in the repository's notebook content and review the reader's question about the stated 12%, 49%, and 54% figures. Done means adding an explanation of how those figures are calculated, if this deprecated repository is still the appropriate place for the update.

Written by the indexing model from the issue text.