Description:

This Master Prompt focuses on the quantitative foundations of Root Cause Analysis for systems characterized by multiple interacting variables, large observational datasets, temporal dependencies, uncertainty and complex fault-propagation behaviour. It guides researchers in transforming raw operational measurements into statistically defensible diagnostic evidence using descriptive statistics, correlation and dependency analysis, multivariate statistical methods, dimensionality reduction, time-series modelling, Granger causality, transfer entropy, Bayesian networks, probabilistic graphical models and other quantitative diagnostic techniques appropriate to the data structure.