There is a question in the Math for Data Scientist → Central Limit Theorem:

“Based on the resulting mean of the sampling distribution, would you say that variance is a biased or unbiased estimator?”

The answer that is provided in the course is:

"Since the mean of the sampling distribution of the variance is not equal to the variance of the population, it is a biased estimator. However, you may notice that it is close! If we set `ddof=1`

in the `np.var()`

function, we can calculate *sample variance*, which is very similar to “population variance” except that the formula has `sample_size - 1`

in the denominator instead of just `sample_size`

. Sample variance is an unbiased estimator of population variance. "

By my understanding the answer saying both - yes, it’s biased and no, it’s unbiased - at the same time))

Could you explain please, what’s going on here? Is sample variance biased or unbiased estimator?