مقایسهٔ روش‌ها

	تحلیل حساسیت با تحلیل درخت رویداد	تحلیل درخت رویداد (ETA)
حوزه	طراحی آزمایش	قابلیت اطمینان
خانواده	Process / pipeline	Process / pipeline
سال پیدایش	Combination formalized in risk and reliability engineering from the 1990s onward	2002
پدیدآور	Sensitivity analysis: Saltelli et al. (1990s–2000s); Event tree analysis: Watson (1961, WASH-1400 formalization 1975)	Andrews & Moss
نوع	Hybrid quantitative risk analysis method	Forward inductive logic tree
منبع بنیادین	Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. Wiley. ISBN: 978-0470059975	Andrews, J. D., & Moss, T. R. (2002). Reliability and Risk Assessment (2nd ed.). Professional Engineering Publishing. ISBN: 978-1-86058-290-5
نام‌های دیگر	SA-ETA, ETA sensitivity analysis, event tree sensitivity analysis, probabilistic sensitivity analysis with ETA	ETA, Event Sequence Diagram Analysis, Initiating Event Analysis, Olay Ağacı Analizi
مرتبط	6	2
خلاصه	Sensitivity analysis with event tree analysis (SA-ETA) is a quantitative risk assessment approach that systematically varies the input probabilities of an event tree model to determine which branch probabilities or initiating event frequencies most strongly influence the calculated probability of undesired outcomes. It extends classical event tree analysis by ranking the uncertainty contributions of individual inputs, thereby guiding risk-reduction efforts toward the parameters that matter most.	Event Tree Analysis (ETA) is a forward inductive technique used in reliability and risk engineering to model the possible outcomes that follow an initiating event. Starting from a single undesired event, ETA traces all subsequent event sequences through a binary branching tree representing the success or failure of safety barriers and protective systems. Introduced formally in reliability and risk literature by Andrews and Moss (2002), it is widely applied in nuclear, chemical, and aerospace industries to quantify accident sequence probabilities and guide safety decision-making.