Answer: 5,767.49

The correct answer is C (5,767.49) as explicitly stated in the text. **Explanation of Biased vs Unbiased Variance Estimators:** - **Biased estimator of variance** uses the formula: $$\sigma^2_{biased} = \frac{\sum_{i=1}^n (x_i - \bar{x})^2}{n}$$ This is biased because it systematically underestimates the population variance. - **Unbiased estimator of variance** uses Bessel's correction: $$\sigma^2_{unbiased} = \frac{\sum_{i=1}^n (x_i - \bar{x})^2}{n-1}$$ This corrects for the bias by dividing by (n-1) instead of n. The difference between these estimators is: $$\sigma^2_{unbiased} - \sigma^2_{biased} = \frac{\sum_{i=1}^n (x_i - \bar{x})^2}{n(n-1)}$$ In this specific question, the numerical difference is given as 5,767.49.

Author: Tanishq Prabhu