Inverse-variance weighting

In statistics, inverse-variance weighting is a method of aggregating two or more random variables to minimize the variance of the weighted average. Each random variable is weighted in inverse proportion to its variance. Given a sequence of independent observations yi with variances σi2, the inverse-variance weighted average is given by The inverse-variance weighted average has the least variance among all weighted averages, which can be calculated as If the variances of the measurements are all equal, then the inverse-variance weighted average becomes the simple average.

Inverse-variance weighting

In statistics, inverse-variance weighting is a method of aggregating two or more random variables to minimize the variance of the weighted average. Each random variable is weighted in inverse proportion to its variance. Given a sequence of independent observations yi with variances σi2, the inverse-variance weighted average is given by The inverse-variance weighted average has the least variance among all weighted averages, which can be calculated as If the variances of the measurements are all equal, then the inverse-variance weighted average becomes the simple average.