Document ID: chunk:federal_register_of_legislation:F2013C00288:reg:1850:p12
Version: federal_register_of_legislation:F2013C00288
Segment Type: reg
Provision Reference: reg 1850 (pt 12/117)
Character Range: 379055–382103

of site investigation. Judgemental sampling is commonly used to investigate sub-surface contamination issues in site assessment.

Although judgemental sampling can invalidate some statistical methods, particularly where the sampling size is small, alternative methods using non-parametric approaches can be used. Further information can be found in Gilbert (1987) and US EPA (2006b, 2007a). Judgemental sampling may be used in combination with other sampling designs to produce effective sampling for defensible decision-making.

    6.2.2          Simple random sampling
In simple random sampling, the selection of samples (number, location, timing, etc.) is based on using random numbers, and all possible selections are equally likely. For example, a simple random sample of a set of drums containing soil for disposal can be taken by numbering all the drums and randomly selecting numbers from that list. Simple random sampling protects against bias (which may occur if sampling locations are subjective) providing that the sample size is not small (more than approximately 20 samples). Many commonly used statistical analysis methods assume that the data was obtained by using a simple random sampling design.

The method is most useful when the area of interest is relatively homogeneous and no major patterns or hotspots are expected. The main advantages of this design are:
    * it provides statistically unbiased estimates of the mean and variability
    * it is easy to understand and implement
    * sample size calculations and data analysis are straightforward.
Information on implementing a simple random sampling approach may be found in US EPA (2006b).
As most site investigations deal with non-uniform distributions of contamination, simple random sampling is usually combined with a stratified approach.

    6.2.3          Systematic and grid  sampling
In systematic and grid sampling, samples are taken at regularly spaced intervals over space or time. An initial location or time is chosen at random or based on a convenient site feature, and then the remaining sampling locations are defined so that all locations are at regular intervals over an area (e.g. grid intersections) or time (systematic). Examples of systematic grids include square, rectangular, triangular, herringbone and radial grids.

Systematic and grid sampling are used to search for hotspots and to infer means, percentiles or other parameters and are also useful for defining spatial patterns or trends over time. If the property/trend of interest is aligned with the grid, systematic/grid sampling has the potential to introduce bias (over or under representation) to the results.

Even though most contamination is not normally distributed, the data can often be transformed to be approximately normal. Also, if data sets are sufficiently large, statistical inferences can still be made, since in that case the sample mean is approximately normally distributed (Gilbert, 1987).

Where a reliable and full site history is available, judgemental sampling