Document ID: chunk:federal_register_of_legislation:F2013C00288:reg:1850:p77
Version: federal_register_of_legislation:F2013C00288
Segment Type: reg
Provision Reference: reg 1850 (pt 77/117)
Character Range: 564244–567139

be corrected whereas the latter can properly be discarded. Following the procedure outlined in Section 13.1 should minimise the impact of outliers from these causes.

If an outlier is not due to human error, then consider the available qualitative information regarding the data provenance and the site history and discard the outlier only if there is documentation to support the belief that the outlier is not part of the population under study. In all such cases, describe the population that the outlier belongs to and justify why this population is not considered relevant to the study objectives (e.g. elevated PAH due to presence of road bitumen fragments as opposed to contamination in soil derived from fuel leaking from an above-ground storage tank).

Discarding an outlier from a data set should be done with extreme caution as environmental datasets often include legitimate extreme values (US EPA 2006b). The decision taken should be based on scientific reasoning and be fully documented. Repeat sampling close (<1 m) to the original location may provide greater certainty in the decision process.

US EPA (2006b) describes several statistical tests for determining whether or not one or more observations are statistical outliers.

    14              Report presentation

14.1          Introduction
An efficient and accurate appraisal of a site requires that the data be collated in a form, or 'model' that facilitates understanding of the location, extent, trends, and likely 'behaviour' of any contamination.
An adequate understanding of what is occurring on a site is almost impossible to achieve from pages of raw data, especially where there are abnormal results or more than a handful of results. At its worst, sample identification numbers, sampling points, geotechnical logs, and results for each analyte will be on separate pages.

A uniform approach to the location and presentation of data makes for more rapid and accurate assessments of reports.

The major problems that can occur with data sets and assessments are:
    * a failure to collate data and to condense it into logical and comprehensible tables
    * cluttered data sets, tables and graphs
    * treating the sum of the data as somewhat greater than the sum of its parts.
This is exemplified by:
    * over-elaborate contour maps (some can be useful) based on a very limited number of data points which are not annotated on the map
    * providing definitive conclusions unsupported by the data
    * considering the numbers in isolation from other data important to interpretation, for example, site history and soil characteristics.

14.2          General requirements
Reports should preferably be printed on A4 size paper, with durable covers and binding which allows for easy opening. Photographs and figures should be of high quality and adequately display the points of interest. Tables and figures