INBIASED ESTIMATE OF GENERAL . VARIANCE sigma ^2 IS ct one: S_(bar (x))=(s)/(sqrt (n)) D(X)=(1)/(N)sum _(i=1)^N(x_(i)-mu )^2 D(X)=(1)/(N)sum _(i=1)^N(x_(i)-mu )^2n_(i) s^2=(n)/(n-1)sigma _(6)^2

The correct answer is:<br /><br />$D(X)=\frac {1}{N}\sum _{i=1}^{N}(x_{i}-\mu )^{2}$<br /><br />This formula represents the general variance, denoted as $\sigma ^{2}$, which is the average of the squared deviations of each data point from the mean $\mu$.