This paper considers the design of acoustic surveys for estimating the mean abundance of spatially correlated populations. We examined how the choice of survey design affects the bias and precision of the sample mean as an estimator of mean abundance. Further, we investigated three different ways of estimating the error variance of the sample mean: the pooled within strata variance and two geos...

Systematic sampling is a commonly used technique due to its simplicity and ease of implementation. The drawback of this simplicity is that it is not possible to estimate the design variance without bias. There are several ways to circumvent this problem. One method is to suppose that the variable of interest has a random order in the population, so the sample variance of simple random sampling ...

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...

1.0 Introduction Systematic sampling (either with equal or unequal selection probabilities) is a common sampling scheme in complex sample designs. It is used because of its simplicity of implementation and its potential increase in efficiency, given a good frame ordering, which acts as an additional stratification. One problem with systematic sampling is that such samples can be viewed as a clu...

This paper presents ‘‘contribution to sample variance plot’’, a natural extension of the ‘‘contribution to the sample mean plot’’, which is a graphical tool for global sensitivity analysis originally proposed by Sinclair. These graphical tools have a great potential to display graphically sensitivity information given a generic input sample and its related model realizations. The contribution t...