Journal
ATMOSPHERIC ENVIRONMENT
Volume 43, Issue 3, Pages 749-752Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2008.10.005
Keywords
Error statistics; Standard deviation; Standard error; Mean-air solute deviation
Funding
- NASA [NNG06GB54G]
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Commonly used sums-of-squares-based error or deviation statistics-like the standard deviation, the standard error, the coefficient of variation, and the root-mean-square error-often are misleading indicators of average error or variability. Sums-of-squares-based statistics are functions of at least two dissimilar patterns that occur within data. Both the mean of a set of error or deviation magnitudes (the average of their absolute values) and their variability influence the value of a sum-of-squares-based error measure, which confounds clear assessment of its meaning. Interpretation problems arise, according to Paul Mielke, because sums-of-squares-based statistics do not satisfy the triangle inequality. We illustrate the difficulties in interpreting and comparing these statistics using hypothetical data, and recommend the use of alternate statistics that are based on sums of error or deviation magnitudes, (C) 2008 Elsevier Ltd. All rights reserved.
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