Geoscience Reference
In-Depth Information
samples is recommended prior to dei ning a suitable sample size.
h e design of the spatial sampling scheme is dependent on the availability
of outcrops or other material suitable for sampling. Sampling in quarries
typically leads to clustered data, whereas sampling along road cuts, shoreline
clif s or steep gorges results in one-dimensional traverse sampling schemes.
A more uniform sampling pattern can be designed where there is 100%
exposure or if there are no i nancial limitations. A regular sampling scheme
results in a gridded distribution of sample locations, whereas a uniform
sampling strategy includes the random location of a sampling point within a
grid square. Although these sampling schemes might be expected to provide
superior methods for sampling collection, evenly-spaced sampling locations
tend to miss small-scale variations in the area, such as thin mai c dykes
within a granite body or the spatially-restricted occurrence of a particular
type of fossil (Fig. 1.2).
h e correct sampling strategy will depend on the objectives of the
investigation, the type of analysis required and the desired level of
coni dence in the results. Having chosen a suitable sampling strategy, the
quality of the sample can be inl uenced by a number of factors resulting in
the samples not being truly representative of the larger population. Chemical
or physical alteration, contamination by other material or displacement by
natural and anthropogenic processes may all result in erroneous results and
interpretations. It is therefore recommended that the quality of the samples,
the method of data analysis employed and the validity of the conclusions
drawn from the analysis be checked at each stage of the investigation.
1.3 Types of Data
Most earth science data sets consist of numerical measurements, although
some information can also be represented by a list of names such as fossils
and minerals (Fig. 1.3). h e available methods for data analysis may require
certain types of data in earth sciences. h ese are
•
nominal data
- Information in earth sciences is sometimes presented as
a list of names, e.g., the various fossil species collected from a limestone
bed or the minerals identii ed in a thin section. In some studies, these data
are converted into a binary representation, i.e.,
one
for present and
zero
for absent. Special statistical methods are available for the analysis of such
data sets.
•
ordinal data
- h ese are numerical data representing observations that
can be ranked, but in which the intervals along the scale are irregularly
