Document ID: chunk:federal_register_of_legislation:F2013C00288:reg:1850:p74
Version: federal_register_of_legislation:F2013C00288
Segment Type: reg
Provision Reference: reg 1850 (pt 74/117)
Character Range: 556028–559193

the scope of this guidance but some general considerations are outlined below. It is the responsibility of the site assessor to ensure that appropriate statistical procedures are followed when comparing site data with the investigation and screening levels listed in Schedule B1 and any site-specific assessment levels.

Evaluation of appropriate summary statistics and graphical displays of the sample data set are recommended for developing an improved understanding of contaminant distribution(s) and to determine whether any investigation and/or screening values have been exceeded.

Many spreadsheet and statistical software packages provide graphical methods, for example boxplots and histograms/frequency distributions, which are suitable for displaying site data. These displays can provide insight into the distribution of the data such as multi-modal, normal, log normal or exponential, which is a necessary precursor for selecting an appropriate statistical approach.

Evaluation of graphical displays such as frequency distributions can also assist the assessor in determining whether the data set should be split up into 'domains of interest' in which there is confidence that homogenous populations of data exist (that is, uni-modal and not bi-or multi-modal distribution) and for which sufficient data for meaningful statistical analysis is available.

Given that much of the sampling in contaminated site assessments is judgemental rather than random, caution needs to be taken when applying conventional (parametric) statistical methods which assume a normal (including log normal) distribution. Non-parametric methods (which do not make the assumption that data is normally distributed) provide an alternative approach for data assessment and may be useful in the early stages of a site assessment when typically there is little data available.

Non-parametric methods rely on 'rank' or 'order' statistics that are simply the percentiles of a distribution. Rather than using the mean to describe the centre of the distribution, non-parametric approaches more commonly use the median or 50th percentile. The difference between the upper quartile (75th percentile) and the lower quartile (25th percentile) is called the 'interquartile range' and is the non-parametric equivalent to the standard deviation for describing the spread of the data about the mean. Boxplots display these key non-parametric statistics and the 'whiskers' show the minimum and maximum of the data. Some software applications also show the position of the arithmetic mean (although this is not a percentile based statistic).

For multiple analytes, the range of concentrations and statistical distribution of results for each assessment area can be presented as in Table 8. Summary statistics should be provided for each soil unit/stratum tested and according to assessment sub-areas or domains of interest, if applicable and where sample size permits.
Table 8: Summary statistics for multiple analytes and assessment areas

Chemical name                                   XXX
Investigation Level:
Number of samples:
Minimum:
 Maximum:
Inter-quartile (25th – 75th percentile)