What distinguishes population variance from sample variance?

The distinction between population variance and sample variance is fundamentally based on the number of data points used in their calculations and the concept of bias in estimators. Population variance is calculated using the actual population data, which includes all possible members of the group being studied. In this case, the population variance formula uses N, where N represents the total number of data points in the population.

In contrast, sample variance is used when you have a subset or a sample of the population, and it serves as an estimate of the population variance. To correct for the bias that could arise from estimating the population variance from a sample, sample variance uses N-1 in its calculations. This adjustment is known as Bessel's correction and helps ensure that the sample variance is an unbiased estimator of the population variance.

The other options do not accurately describe the differences between population variance and sample variance. For instance, population variance is not calculated using median values; it is based on the mean of the data. Also, while the sample variance can be greater than or less than the population variance depending on the sample size and the data distribution, it is not inherently stated that it is always greater. Lastly, the assertion that there is no difference in calculation is incorrect, as they rely on