Sentence examples for a population parameter from inspiring English sources

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.

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.

Bayesian methods (so called after the English mathematician Thomas Bayes) provide alternatives that allow one to combine prior information about a population parameter with information contained in a sample to guide the statistical inference process.

The concept of a marginal likelihood is best illustrated for a model with a single population parameter (Supplementary Data online).

For a single population parameter of interest, Q, e.g. a regression coefficient, the MI overall point estimate is the average of the m estimates of Q from the imputed datasets, [ 4].

The essential idea is to use a statistic for a representative sample to estimate an unknown population parameter.

Reproduction is a relevant population parameter because it is relatively easy to measure in the field and is a vital component directly affecting population dynamics.

They target a conditional population parameter.