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With the HFM it is possible to determine the moments of the estimate error (systematic value and covariance matrix) as a function of the inspection plan.
Epidemiologic studies are subject to two types of error: systematic and random.
Each NGS technology displayed some intrinsic properties, i.e. base calling error, systematic bias, etc.
The unusually large genetic differentiation between these populations was not due to genotyping error, systematic artifacts, or sampling bias.
There are two components of variability associated with each assessment of measurement error: systematic bias (i.e. changes in a measure over time such as learning effects) and random error due to inherent subject or instrument variation [ 26].
However, stochastic error, systematic error and non-phylogenetic signal can also lead to low node support [ 12, 59], as observed in the lack of phylogenetic resolution among the major lineages of Ovalentaria.
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Finally, since health care services can only be evaluated by empirical measurements, inevitably there will be errors (systematic and random).
The matrix is constructed from the three dimensions of errors: systematic error ('bias'), random error ('play of chance'), and design error ('wrong design to answer the question posed' or 'wrong context').
Besides all instrumental errors, systematic errors were estimated to be mainly due to incomplete mixing of the samples with the solvent as well as due to evaporation of Cd.
In contrast to stochastic errors, systematic errors cannot be mitigated but may be highlighted by increasing characters in phylogenomic analyses (Delsuc et al. 2005; Jeffroy et al. 2006; Telford and Copley 2011).
Random departures from the theory could just be error, but systematic departures are worth studying.
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