Robust measures of scaleIn statistics, robust measures of scale are methods that quantify the statistical dispersion in a sample of numerical data while resisting outliers. The most common such robust statistics are the interquartile range (IQR) and the median absolute deviation (MAD). These are contrasted with conventional or non-robust measures of scale, such as sample standard deviation, which are greatly influenced by outliers.
Chemical substanceA chemical substance is a form of matter having constant chemical composition and characteristic properties. Chemical substances can be simple substances (substances consisting of a single chemical element), chemical compounds, or alloys. Chemical substances that cannot be separated into their simpler constituent elements by physical means are said to be 'pure'; this notion intended to set them apart from mixtures.
Species PlantarumSpecies Plantarum (Latin for "The Species of Plants") is a book by Carl Linnaeus, originally published in 1753, which lists every species of plant known at the time, classified into genera. It is the first work to consistently apply binomial names and was the starting point for the naming of plants. Species Plantarum was published on 1 May 1753 by Laurentius Salvius in Stockholm, in two volumes. A second edition was published in 1762–1763, and a third edition in 1764, although this "scarcely differed" from the second.
Ring speciesIn biology, a ring species is a connected series of neighbouring populations, each of which interbreeds with closely sited related populations, but for which there exist at least two "end populations" in the series, which are too distantly related to interbreed, though there is a potential gene flow between each "linked" population and the next. Such non-breeding, though genetically connected, "end populations" may co-exist in the same region (sympatry) thus closing a "ring".
Harmonic mean p-valueThe harmonic mean p-value (HMP) is a statistical technique for addressing the multiple comparisons problem that controls the strong-sense family-wise error rate (this claim has been disputed). It improves on the power of Bonferroni correction by performing combined tests, i.e. by testing whether groups of p-values are statistically significant, like Fisher's method. However, it avoids the restrictive assumption that the p-values are independent, unlike Fisher's method.
