Relative efficiency of estimators of the common mean of possibly different normal populations N(μ, σi2) is investigated empirically. A weighted least squares estimator , with weights based on a modification of minimum norm quadratic unbiased (MINQU) estimators of the σi2, is found to be substantially more efficient than the maximum likelihood (ML) estimator of μ when the heterogeneity in the σi, is small to moderate and the number of sample observations from a population is small. The jackknife t statistic for performed well in regard to both coverage probability and expected length of the confidence interval.