Much attention has been given to sampling design, and the sampling method chosen directly affects the sampling accuracy. The development of spatial sampling theory has lead to the recognition of the importance of taking spatial dependency into account when sampling. This text uses the new Sandwich Spatial Sampling and Inference (SSSI) software as a tool to compare the relative error, coefficien...

The present study investigated the relationship between emotional intelligence and the general health among delinquents and normal juveniles in Iran. The design of this study was ex-post facto design. Using a random stratified sampling technique from five districts of Iran, west, East, Norrth, South and the center: 339 juveniles (161 normal and 178 delinquent juveniles) were selected from it. A...

Supporting sampling in the presence of joins is an important problem in data analysis. Pushing down the sampling operator through both sides of the join is inherently challenging due to data skew and correlation issues between output tuples. Joining simple random samples of base relations typically leads to results that are non-random. Current solutions to this problem perform biased sampling o...

We look at the benefits of using a kind of quasi-random numbers to obtain more accurate results for a given number of simulation runs. We explore a sampling method with enhanced independence in multidimensional simulations by combining the ideas of stratified sampling and Latin Hypercube sampling. We test the new sampling method by comparing it with traditional stratified sampling and Latin Hyp...

OBJECTIVES Providing high service quality is one of the main functions of health systems. Measuring service quality is the basic prerequisite for improving quality. The aim of this study was to evaluate the quality of service in teaching hospitals using importance-performance analysis matrix. METHODS A descriptive-analytic study was conducted through a cross-sectional method in six academic h...

In this article, we propose an improved estimator for finite population variance based on stratified sampling by using the auxiliary variable as well rank of variable. Expressions bias and mean square error estimators are derived up to first order approximation. Four real data sets used measure performances estimators. Moreover, a simulation study is also conducted observe efficiency proposed e...

In this paper we investigate the problem of estimation finite population mean using auxiliary information. The aim is to modify a separate ratio estimator by calibration approach for stratified random sampling. We use improve precision estimate parameter incorporating chi-square distance function minimize between original design weight and new weight. two constraints called equations find weigh...