The phrase "a function of the sample size" is correct and usable in written English.
It can be used in statistical or research contexts to describe how a particular outcome or measurement depends on the size of the sample being analyzed.
Example: "The accuracy of the results is a function of the sample size, meaning larger samples tend to yield more reliable data."
Alternatives: "dependent on the sample size" or "related to the sample size".
Empirical expressions are derived for determining the A-basis and the B-basis material properties as a function of the sample size.
Effective elastic and plastic mechanical properties of Voronoi samples are calculated as a function of the sample size, and deformation mechanisms triggering the size effects are traced through strain maps.
This calculation makes possible the measurement of a potential real significance of the effect of the intervention in each group, by describing the size of the observed effect, which is independent of a possible misleading effect as a function of the sample size (Lindenau & Guimarães, 2012).
However, the HSp is simply a function of the sample size and diagnostic test specificity.
Herd-level sensitivity (HSe), which is the probability that a seropositive herd is correctly classified as seropositive, is a function of the sample size, diagnostic test sensitivity, sample interpretation and importantly, within herd animal-level prevalence.
This indicates the degree of uncertainty in the range values and is a function of the sample size.
The certainty with which θ is estimated is reflected in sθ which is a decreasing function of the sample size.
We assumed that the discriminatory ability of a model is a monotonically increasing function of the sample size, converging to a maximum at the infinite sample size.
The effective spatial resolution is a function of the sample under study, the AFM tip size and the sampling frequency.
This is however, partly due to the fact that statistical significance, and p-values, are functions of the sample size.
The power is a function of sample size and effect size (the parameters a and b in Eqs. 6– 8): The more samples are available and the larger the effect size, the higher to probability to discover a relevant feature.
