Estekarvo

Estekarvo is a term used in statistics to denote the estimated value of a population parameter obtained from a sample using a statistical estimator. It is the concrete numerical output produced by applying the estimator to observed data. The true parameter value is unknown, and the estekarvo serves as an approximation.

An estimator is a rule T(X1, ..., Xn) for a parameter θ. The estekarvo is the realized value T(X1, ..., Xn) after observing the sample. Estekarvo can be biased or unbiased, consistent or inconsistent, depending on the estimator and the model. Common examples include the sample mean as an estekarvo for the population mean, the sample proportion as an estekarvo for a population proportion, and the maximum likelihood estimator's value for a parameter. In Bayesian analysis, the posterior mean or median can be interpreted as an estekarvo under a specified loss function.

Key properties of estekarvo include bias, variance, and mean squared error. An unbiased estekarvo has expected value equal to θ; a consistent estekarvo converges to θ as sample size increases. In practice, estekarvo is reported with measures of uncertainty, such as confidence intervals or credible intervals, to reflect sampling variability and model assumptions.

Estekarvo plays a central role in hypothesis testing, interval estimation, and decision-making under uncertainty, bridging observed data and the unknown parameter. It is a core concept in both frequentist and Bayesian inference contexts.