# Sample variance expectation

## Main Question or Discussion Point

It is defined that the population variance is $$S^{2}= \frac{1}{N-1}\sum^{N}_{1}\left(y_{i} - \bar{y}_{N}\right)^{2}$$ or $$\sigma^{2}= \frac{1}{N}\sum^{N}_{1}\left(y_{i} - \bar{y}_{N}\right)^{2}$$.

Also that the $$V\left[\bar{y}_{n}\right] = \frac{N-n}{N}\frac{S^{2}}{n} = \left(\frac{1}{n} - \frac{1}{N}\right)S^{2}$$ and its unbiased estimator is $$\hat{V}\left[\bar{y}_{n}\right] = \frac{N-n}{N}\frac{s^{2}}{n} = \left(\frac{1}{n} - \frac{1}{N}\right)s^{2}$$ where $$s^{2}= \frac{1}{n-1}\sum^{n}_{1}\left(y_{i} - \bar{y}_{n}\right)^{2}$$

To show that $$\hat{V}\left[\bar{y}_{n}\right]$$ is unbiased, I understand that we only need to show that $$E\left[s^{2}\right] \right]= S^{2}$$

I have done like this $$E\left[s^{2}\right] \right]$$ = $$E\left[\frac{1}{n-1}\sum^{n}_{1}\left(y_{i} - \bar{y}_{n}\right)^{2}\right]$$ and I have arrived at $$\left(n-1\right)E\left[s^{2}\right] = nE\left[y^{2}_{i}\right] - nE\left[\bar{y}^{2}_{n}\right]$$ and come up at $$E\left[s^{2}\right] \right]= \sigma^{2}$$

My question is why I did not come up at $$S^{2}$$ as the $$E\left[s^{2}\right]$$?