Document ID: chunk:federal_register_of_legislation:F2013C00288:reg:1850:p75
Version: federal_register_of_legislation:F2013C00288
Segment Type: reg
Provision Reference: reg 1850 (pt 75/117)
Character Range: 558868–561813

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) range:
Median (50th percentile):
Arithmetic mean:
Arithmetic standard deviation:
Geometric mean:
Geometric standard deviation:
95% Upper Confidence level (UCL)
Frequency distributiona                         Number  %
Less than investigation level:
> 1 and < 2 times investigation level:
>2 and <5 times investigation level:
>5 and < 10 times investigation level:
>10 times investigation level:

a: An arbitrary method used to categorise data.

Maximum observed contaminant concentration—This generally provides a conservative assessment of exposure because if estimated risks from the maximum concentrations are not of concern, then the site should be suitable for the land use scenario(s) considered. However, a maximum concentration may not be representative of the source as a whole and may result in an overestimation or underestimation of risk if the data is extremely limited.
Mean concentration — The mean contaminant concentration can be a suitable metric provided that it can be shown that it adequately represents the source being considered. It is important that small areas of high concentrations or hotspots are not ignored by averaging with lower values from other parts of the site. The mean value may be more representative of the source as a whole than the maximum, and may provide a better estimation of the actual concentration that a population would be exposed to over a period of time.

The 95% upper confidence limit (UCL) of the arithmetic mean contaminant concentration provides a 95% confidence level that the true population mean will be less than, or equal to this value. The 95% UCL is a useful mechanism to account for uncertainty in whether the data set is large enough for the mean to provide a reliable measure of central tendency. Note that small data sets result in higher 95% UCLs.

The procedure for calculating the 95% UCL of the arithmetic mean and also of the mean for a log normal distribution is provided in NSW EPA (1995).

Further information on understanding data distributions and statistical procedures can be found in Gilbert (1987), US EPA (2006b) and in the ProUCL user guide US EPA (2007a).

    13.2.2      Censored data
Source US EPA (2006b)
Data generated from chemical analysis may fall below the limit of detection (LOD) or limit of reporting, (LOR) of the analytical procedure. These measurement data are generally described as 'non-detects' rather than 'zero' or 'not present' and the appropriate limit of detection for the analytical procedure should be reported. Data that includes both numerical data and 'non-detect' results is referred to as censored data