Abstract: Events and metrics from time series data are analyzed to detect unexpected spikes and dips or other unpredictable occurrences. In time series measurement of a metric it is not uncommon for a particular metric to have predictable deviations from a median value. For example, activity on a particular “weekday” web site may be more intense during weekdays and have very little activity on weekends. A different web site might have the opposite “normal” activity profile. If the “weekday” web site were to have a large amount of activity on a Saturday and/or Sunday then that large amount of activity may be considered unpredictable and be classified as a “suspect anomaly.” Techniques to identify and novel presentation of suspect anomalies are presented in this disclosure.