Methoden vergleichen

	Monte-Carlo-Simulation	Permutationstest (Randomisierungstest)
Fachgebiet	Entscheidungsfindung	Statistik
Familie	MCDM	Regression model
Entstehungsjahr	1949	2005
Urheber	Metropolis, N., Ulam, S.	Good (2005); Edgington & Onghena (2007); resampling tradition
Typ	Robustness wrapper — Monte Carlo uncertainty propagation	Nonparametric resampling test
Wegweisende Quelle	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association	Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792
Aliasnamen	—	randomization test, exact permutation test, re-randomization test, Permütasyon Testi
Verwandt	0	5
Zusammenfassung	MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value.