The statistical approach definitely gives a developer more confidence in the correctness of a solution and guards against regressions. Though any test that checks the outcome of a random process against statistical measures is expected to fail occasionally.

For example, if the test flips the coin 1,000 times, there is better than a 99% chance that the outcome would result in 450 to 550 heads. So if you write the test using `450 <= heads <= 550`, you know that it will fail ~1% of the time. And if you expand the range to reduce the rate of false negatives, you have reduced the confidence the test is validating correctness.

Having said that, I still find statistical tests to be very helpful when building out code that uses randomness. However, these tests typically do not make it into the CI/CD pipeline.