Stratified sampling is often used in opinion polls to reduce standard errors, and it is known as variance reduction technique in sampling theory. The most common approach of resampling method is based on bootstrapping the dataset with replacement. A main purpose of this work is to investigate extensions of the resampling methods in classification problems, specifically we use decision trees, fr...

The problem of estimating the population mean in un-stratified sampling strategies to estimate the finite the presence of an auxiliary variable has been widely discussed in finite population sampling literature [1], suggested a class of estimators of the population mean using one auxiliary variable in the stratified random sampling and examined the MSE of the estimators up to the kth order of a...

be transferred and processed increases proportionally to the number of packets measured. High packet rates elevate the resource consumption and with this the costs for the measurement process. Since measurement costs should be only a small fraction of the service provisioning costs itself, there is a strong incentive for limiting the needed measurement resources and lowering the associated cost...

Any pl-stratified pseudomanifod can be normalized preserving its intersection homology. In this paper we extend this result for any topological stratified pseudomanifold and for a family of perversities which is larger than usual. Our construction is functorial. We also give a detailed description of the normalizer’s stratification in terms of the initial stratified pseudomanifold.

This article reviews the preliminary results of a five-year Technology Innovation Challenge Grant initiative in North Dakota. A stratified sample of 72 schools was selected from the 423 schools participating. Data on the competencies of the leadership within each school (both administrators and mentors) was compared to technology integration success factors of the teachers associated with the l...