so is the conclusion to be that statistically significant sample size is as important as the 'result' when measuring standard deviation?
The point of this article is that a sample only accurately reflects the whole in some ways. Variability in particular scales with the square root of the sample size. And since misconceptions about variability have been at the heart of many controversies (male vs. female intelligence, school size, cancer risk, etc.), De Moivre's equation is important; even dangerous in the sense that ignorance of it has led to billions of dollars wasted.