Updating mean and variance estimates an improved method
A better quantity for updating is the sum of squares of differences from the current mean, This algorithm is much less prone to loss of precision due to catastrophic cancellation, but might not be as efficient because of the division operation inside the loop.
For a particularly robust two-pass algorithm for computing the variance, one can first compute and subtract an estimate of the mean, and then use this algorithm on the residuals.
Without keeping an eye on the actual costs while the project is being implemented, the project will most likely never be delivered on-budget.
The following formulas can be used to update the mean and (estimated) variance of the sequence, for an additional element x These formulas suffer from numerical instability, as they repeatedly subtract a small number from a big number which scales with n.In any case the second term in the formula is always smaller than the first one therefore no cancellation may occur.However, the results of both of these simple algorithms ("naïve" and "two-pass") can depend inordinately on the ordering of the data and can give poor results for very large data sets due to repeated roundoff error in the accumulation of the sums.Preventative and corrective actions are determined based on the variance analysis.Performance reviews in projects are required to check the health of a project.