Besset Correction

Review and intuition why we divide by n-1 for the unbiased sample | Khan Academy - YouTube

Naiive sample variance estimator:

$${\hat{s}}^2=\frac{{\sum }_{i=1}^n(x_i-\bar{x})}{n}$$

⇒ Sample variance is biased. (btw, this is MLEs) Besset Corrected sample variance estimator:

$${\hat{s}}^2=\frac{{\sum }_{i=1}^n(x_i-\bar{x})}{n-1}$$

• Larger than the naiive sample estimator