Meaning
Part of the formula for calculating dispersion determines the weighting of individual differences from the average. This specific value is the variance denominator. It adjusts the scale of the resulting figure to account for the limited number of samples in the set.
Degree Adjustment
Subtracting one from the total count of observations accounts for the fact that the sample mean is used in the calculation. This adjustment is necessary to ensure that the variance denominator produces a result that is not artificially low. It reflects the mathematical constraint that the last piece of data is not free to vary once the mean is known.
Every extra observation increases the degrees of freedom within the statistical model.
Bias Correction
Using the correct divisor prevents the systemic underestimation of volatility when working with limited data. In the early days after founding, when the number of data points is low, the impact of this correction is most pronounced. It ensures that the risks of the operation are not hidden by a faulty calculation.
Sample Size
Sample size matters. Increasing the number of observations makes the difference between using N and N minus one in the variance denominator less apparent. As the organization grows and more data is collected, the calculation becomes more stable.
The denominator eventually becomes large enough that the estimate of variance converges on the true value.
