Teststatistiker

Teststatistiker, or test statistician in German-speaking contexts, is a statistician who focuses on the design, evaluation, and application of test statistics used in hypothesis testing and decision-making under uncertainty. The central task is to construct functions of data—test statistics—that help decide between competing hypotheses and to characterize their behavior under both null and alternative scenarios.

Core activities include deriving sampling distributions, computing properties such as bias, variance, and efficiency, and assessing power and robustness. Teststatistikers often use simulation (Monte Carlo methods) and asymptotic theory to study finite-sample performance and to compare competing tests. They implement tests in statistical software and collaborate with researchers to select or tailor statistics for specific experimental designs or regulatory requirements.

Applications span biomedical research, psychology, economics, quality control, and industrial engineering, where reliable decision rules are needed despite variability and limited data.

Educational background typically includes an advanced degree in statistics or a closely related field, with emphasis on mathematical theory, probability, inference, and computational methods. The role combines theoretical work with practical data analysis and programming in R, Python, SAS, or Stata.

See also hypothesis testing, test statistic, and power analysis.