A key, and somewhat controversial, feature of Bayesian methods is the notion of a probability distribution for a population parameter.
This work does not consider consolidation (correlation between traits), a population parameter that is essential to network formation and diffusion.
The dependence of rogue wave profiles on the electron beam and energetic population parameter are discussed.
Hypothesis testing is a form of statistical inference that uses data from a sample to draw conclusions about a population parameter or a population probability distribution.
Sampling error is the difference between a population parameter and a sample statistic used to estimate it.
Knowledge of the sampling distribution is necessary for the construction of an interval estimate for a population parameter.
The main finding indicated that the sample prevalence of 0% was statistically lower than the null population parameter of 3%.
The diagnostic compares finite population parameter estimates and can be calculated from quantities related to the full data set.
The essential idea is to use a statistic for a representative sample to estimate an unknown population parameter.
Bayesian analysis, a method of statistical inference (named for English mathematician Thomas Bayes) that allows one to combine prior information about a population parameter with evidence from information contained in a sample to guide the statistical inference process.
(e), Representative solution of excitatory (left) and inhibitory (right) population (parameter setting: aee = 22.2, aei = aie = 21.6, aii = 20.8, σe = 1.9 σei = 1.4, σii = 0.6); simulations performed on a 80×80 grid, see Methods).
