For a random variable $X$ with finite variance and nonzero mean, its relative variance is $R_X=\mathrm{Var}(X)/(\mathbb{E}X{)}^2$. It equals the square of the coefficient of variation under the usual positive-mean convention. Multiplying $X$ by a nonzero constant leaves $R_X$ unchanged; adding a constant generally does not.

For an average of $n$ independent identically distributed observations with mean $\mu \ne 0$ and variance ${\sigma }^2$, the relative variance is ${\sigma }^2/(n{\mu }^2)$. Chebyshev's inequality gives $\mathbb{P}(|X/\mathbb{E}X-1|\ge a)\le R_X/a^2$, explaining its role in self-averaging. At zero mean the ratio is undefined, so another reference scale is needed.

A seed dispersal syndrome is a combination of seed or fruit traits associated with a mode of seed dispersal. Wings can favor transport by wind, while fleshy fruits can attract animals that later deposit the enclosed seeds. The traits generate a hypothesis about likely transport, not direct proof of the agent responsible for every dispersal event.

A comparative study connecting fruit traits with observed disperser networks found that morphological traits better supported broad groups of dispersing birds, terrestrial mammals and bats than chemical or display traits did.^[ref] Direct observations remain valuable because removal of a fruit, deposition of a viable seed and establishment after germination are different stages of successful seed dispersal.

Liquid scintillation counting measures radiation through light produced in a liquid scintillator containing the radioactive sample. Energy deposited in the medium leads to optical emission, which photomultipliers detect as pulses. The apparatus is a scintillation counter, but the measured pulse rate still needs a model connecting it to radioactive activity.^[ref]

In an idealized one-count-per-decay model with background subtracted and other corrections negligible,where $A$ is radioactive activity and $\epsilon$ is detection efficiency. A hypothetical net rate of $100{\mathrm{s}}^{-1}$ with $\epsilon =0.40$ corresponds to $A=250\mathrm{Bq}$. At the same activity, an efficiency of $0.20$ would produce only $50{\mathrm{s}}^{-1}$. A smaller count rate need not mean that fewer decays occur.

A motivating measurement example is L. L. Lucas's comparison of tritium-containing water standards. Liquid scintillation counting supplied massic activity ratios that could be compared with independently recorded mass-based dilutions. Agreement within stated measurement uncertainties supports consistency of the standards; it does not turn the counting apparatus into an uncertainty-free activity meter.^[ref]