This paper aims to compare stratified random sampling and stratified ranked
set sampling. A simulation study was conducted to evaluate the performance
of the parameter estimates on both sampling techniques. Population sizes,
sampling rates, stratum sizes, and correlation of the target variable and
concomitant variable were varied, nonparametric bootstrap was then used in
estimating the mean and its standard error. The coefficient of variation (CV)
and the bias of the bootstrap estimates were compared. Stratified ranked set
sampling generally outperforms stratified random sampling in terms of bias
most especially for small populations. The two sampling designs were used in
estimating the average mango production per barangay in the country