1. A computer-implemented method for identifying noise in inspection data, comprising: detecting events in sets of inspection data using detection parameters known to detect noise, nuisance events, and real events, wherein the sets of inspection data are generated by different inspections performed on a specimen in a single inspection process; identifying the events detected in a number of the sets of inspection data that is less than a predetermined number as noise; determining one characteristic of the real events; determining the real events having the greatest diversity of the one characteristic; selecting the real events having the greatest diversity of the one characteristic for defect analysis; and binning the real events into one or more groups based on proximity of the real events to each other on the specimen and spatial signatures formed by the one or more groups, wherein the binning comprises spatial signature analysis, wherein the spatial signature analysis comprises stacking the inspection data corresponding to multiple areas on the specimen, wherein the multiple areas comprise the same patterned feature design, wherein the spatial signature analysis further comprises determining the proximity of the real events to each other on the specimen and the spatial signatures formed by the one or more groups based on the stacked inspection data, and wherein said detecting, said identifying, said determining the characteristic, said determining the real events, said selecting, and said binning are performed using a computer system.