Ersatzwerte
Ersatzwerte, in statistics and data processing, are substitute values used to replace data points that are missing, uncertain, or temporarily unavailable. They enable analyses, modeling, and computations that require complete data sets or continuous numeric streams. Ersatzwerte can be applied in various contexts, including data imputation, measurement, and programming, where a placeholder value is needed to indicate a special condition or to reserve a slot in a data structure.
In data analysis, researchers choose Ersatzwerte with awareness of potential bias. Common approaches include simple imputation
Sentinel values in programming also serve as Ersatzwerte, used to mark missing data, end-of-list, or error conditions.
Important considerations include the mechanism causing missingness (missing completely at random, missing at random, or not
In practice, Ersatzwerte appear in survey data, sensor networks, clinical trials, and econometric modeling, where complete
See also: missing data, imputation, sentinel value, data quality.