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Diagnostic terms
Root cause, cohorts and anomaly detection: why it happened.
Anomaly detection Identifying data points or patterns that deviate significantly from expected or normal behavior. Change-point detection Identifying the points in a time series where its underlying statistical behavior shifts abruptly rather than drifting gradually. Correlation A statistic between -1 and 1 that measures the strength and direction of a linear relationship between two variables. Diagnostic analytics Analytics focused on explaining why something happened by drilling into patterns, correlations, and root causes behind results. Outlier An observation that differs markedly from the rest of the dataset, either from genuine variation or from an error. Pareto analysis A technique that ranks causes or categories by their contribution to a problem, to focus effort on the small number responsible for most of it. Root cause analysis (RCA) A structured process for tracing a problem back through its contributing factors to the underlying cause, not just its symptoms. Sampling bias A systematic distortion that arises when the method used to select a sample favors some members of the population over others. Selection bias A distortion that occurs when the sample analyzed is not representative of the population it is meant to describe. Simpson's paradox A pattern where a trend appears in several groups of data but reverses or disappears when the groups are combined. Spurious correlation A statistically strong relationship between two variables that has no causal or meaningful connection. Survivorship bias A distortion that occurs when analysis focuses only on entities that "survived" a filter, ignoring those that failed or dropped out.