Geoscience Reference
In-Depth Information
1.2 Data Collection
Most data sets in earth sciences have a very limited sample size and also
contain a signii cant number of uncertainties. Such data sets are typically
used to describe rather large natural phenomena, such as a granite body, a
large landslide or a widespread sedimentary unit. h e methods described
in this topic aim to i nd a way of predicting the characteristics of a larger
population
from a much smaller
sample
(Fig. 1.1). An appropriate sampling
strategy is the i rst step towards obtaining a good data set. h e development
of a successful strategy for i eld sampling requires decisions on the
sample
size
and the
spatial sampling scheme
.
h e sample size includes the sample volume, the sample weight and the
number of samples collected in the i eld. h e sample weights or volumes can
be critical factors if the samples are later analyzed in a laboratory and most
statistical methods also have a minimum requirement for the sample size.
h e sample size also af ects the number of subsamples that can be collected
from a single sample. If the population is heterogeneous then the sample
needs to be large enough to represent the population's variability, but on
the other hand samples should be as small as possible in order to minimize
the time and costs involved in their analysis. h e collection of smaller pilot
Fig. 1.1
Samples and populations. Deep valley incision has eroded parts of a sandstone
unit (
hypothetical population
). h e remaining sandstone (
available population
) can only be
sampled from outcrops, i.e., road cuts and quarries (
accessible population
). Note the dif erence
between a statistical sample as a representative of a population and a geological sample as a
piece of rock.
