Причина отмены This guide covered the evaluation of sample data that contain a high level of uncertainty for decision-making purposes and, where it is feasible, how to design a statistical study to estimate and reduce the sources of uncertainty in waste-management decision-making.

Formerly under the jurisdiction of Committee D34 on Waste Management, this guide was withdrawn in May 2015. This standard is being withdrawn without replacement due to its limited use by industry.

Значение и использование

This guide will evaluate sample data that contain a high level of uncertainty for decision-making purposes and, where it is feasible, design a statistical study to estimate and reduce the sources of uncertainty. Oftentimes, historical data may be available and adequate for this purpose and no new study is needed.

3.1.1 This approach will help the stakeholders better understand where the greatest sources of uncertainty are in the sampling and analysis process. Resources can be directed to where they can most reduce the overall uncertainty.

3.1.2 Sampling and analysis design under this approach can often be cost-efficient because (a) the reduction in uncertainty can be done by statistical means alone and (b) the reduction can be translated into a lower number of analyses.

This guide is limited to the situation where a decision is based on the mean of a population. It will only include discussions of a balanced design for the collection and analysis of sample data in order to estimate the sources of uncertainty. References to unbalanced designs are provided where appropriate.

Область применения

1.1 Waste management decisions generally involve uncertainty because of the fact that decisions are based on the use of sample data. When uncertainty can be reduced or controlled, a better decision can be achieved. One way to reduce or control uncertainty is through the estimation and control of the components contributing to the overall uncertainty (or variance). Control of the sizes of these variance components is an optimization process. The optimizations results can be used to either improve an existing sampling and analysis plan (if it should be found to be inadequate for decision-making purposes) or to optimize a new plan by directing resources to where the overall variance can be reduced the most.

1.2 Estimation of the variance components from the total variance starts with the sampling and measurement process. The process involves two different kinds of uncertainties: random and systematic. The former is associated with imprecision of the data, while the latter is associated with bias of the data. This guide will discuss only sources of uncertainty of a random nature.

1.3 There may be many sources of uncertainty in waste management decisions. However, this guide does not intend to address the issue of how these sources are identified. It is the responsibility of the stakeholders and their technical staff to analyze the sampling and measurement processes in order to identify the potentially significant sources of uncertainty. After identifying these sources, this guide will provide guidance on how to collect and analyze data to obtain an estimate of the total uncertainty and its components.