In variance calculation, what is divided by the number of samples minus one?

In variance calculation, the correct approach involves dividing the sum of the squared differences from the mean by the number of samples minus one. This method is used to provide an unbiased estimate of the population variance from a sample. The squared differences from the mean are obtained by taking each individual sample value, subtracting the mean of the sample, squaring the result, and summing all these squared values.

When calculating variance from a sample rather than a whole population, dividing by the number of samples minus one (also known as Bessel's correction) corrects the bias that can occur in variance estimation. By doing this, one compensates for the fact that using a sample tends to underestimate the variance of the entire population.

Therefore, recognizing that the variance formula specifically requires the squared differences to be divided by the number of samples minus one is essential for achieving an accurate representation of variability within the data. This correction ensures that the results are more generalizable and provides a more reliable estimate of the population variance when only a sample is available.