Any attempt to assess species abundances must employ a sampling design that balances collection of accurate information for many species with a reasonable sampling effort. To assess the accuracy of commonly used within-site sampling designs for sessile species, we gathered cover data at 2 rocky intertidal locations in Southern California using a high-density point-contact method that maintained...

INTRODUCTION The study of the distribution of any variable in marine environment generally begins by a sampling experiment. Usually, the collection of samples follows a procedure, often fixed in advance, that takes into account the general distribution of the water masses for a given region. However, much attention may be devoted to the actual structure of the water column present below the shi...

Stratified random sampling (SRS) is a fundamental sampling technique that provides accurate estimates for aggregate queries using a small size sample, and has been used widely for approximate query processing. A key question in SRS is how to partition a target sample size among different strata. While Neyman allocation provides a solution that minimizes the variance of an estimate using this sa...

A major challenge in network and service level agreement (SLA) management is to provide Quality of Service (QoS) demanded by heterogeneous network applications. Online QoS monitoring plays an important role in the process by providing objective measurements that can be used for improving network design, troubleshooting and management. Online QoS monitoring becomes increasingly difficult and com...

Sensitivity analysis is a key part of a comprehensive energy simulation study. Monte-Carlo techniques have been successfully applied to many simulation tools. Several sampling techniques have been proposed in the literature; however to date there has been no comparison of their performance for typical building simulation applications. This paper examines the performance of simple random, strati...

The paper presents a model that extends the stochastic finite element method to the modelling of transitional energetic–statistical size effect in unnotched quasibrittle structures of positive geometry (i.e. failing at the start of macro-crack growth), and to the low probability tail of structural strength distribution, important for safe design. For small structures, the model captures the ene...

A comparison is made between the variance of the estimator of the total of a variable obtained from both a simple and a stratified random sampling, in which the sample sizes of some strata are equal to the stratum population size. It is shown that in this case, the advantage of the stratified sample could depend on the sample size. The paper presents inequalities that determine, as a function o...

This study investigated principals’ leadership styles and teachers’ job performance in senior secondary schools in Ondo State, Nigeria. The study population comprised all the 281 secondary schools in the State. Out of this population, a sample of 240 senior secondary schools was taken and selected through the stratified random sampling technique. Out of the 7460 teachers (including principals) ...

We propose a jackknife variance estimator for the population average from two, two-phase samples after imputation. The jackknife method has long been used to estimate and reduce bias, but has now become a valuable tool for variance estimation. We apply two different sampling methods, (simple random sampling and stratified random sampling) to derive jackknife variance estimators for the twosampl...

Software reliability testing provided the necessary guarantee for improving software reliability level and estimation. The traditional method for generating software reliability test cases could be seen as a simple random sampling, which was randomly choosen according to the operational profile defined by Musa. The stratified sampling was well known as a complex but more accurate sampling appro...