First, the biological implication of the error-threshold is that it hampers the accumulation of information through increasing the genome size of the replicators [ 1, 4].
Although weather data are widely acknowledged to contain measurement errors, the implications of these errors for models that relate weather to yields have not been adequately examined.
The implications of these errors can be profound because many conservation plans for endangered wildlife are based on habitat use patterns derived from movement data [17].
Implications of these errors for large‐scale, multiple slide and multiple laboratory experiments are discussed.
It is also important to emphasise that this work entirely separates random and systematic error and relates only to the implications of random error in the sense that it is assumed that any errors in measuring a variable are independent of the value of other variables.
In the case where the implications of an error are very serious (eg, missing the diagnosis of a cancer), different alpha and beta levels might be appropriate in the study design to assess clinical or biological significance.
We investigated the sources and implications of georectification error in the measurement of lateral channel movement by testing how the number (6 30) and type (human versus natural landscape features) of ground-control points (GCPs) and the order of the transformation polynomial (first-, second-, and third-order) affected the spatial accuracy of a typical georectified aerial photograph.
By contrast, assessments of the implications of observation error (arising from sampling limitations) for model precision are often lacking, but see [6], [7], perhaps due to a widespread acknowledgement of the ubiquity of sampling constraints [8].
It is therefore important to have some appreciation of the implications of measurement error for DSS study results and tolerable levels of errors and missing data.
Awareness of the implications of genotyping error has increased greatly in recent years, and there is an emerging consensus that error rates should be estimated and reported, particularly when performing error-sensitive analyses such as parentage analysis or individual identification (Bonin et al. 2004; Hoffman and Amos, 2005; Pompanon et al. 2005; DeWoody et al. 2006).
