**4. Conclusions**

Both correlation and coherence show when two, or more, time-series behave similarly in the time domain, according to shape (correlation) or frequency composition (coherence). Thus, these techniques allow the identification of time-domain anomalies, i.e. periods in time when the common behaviour of two, or more, time-series changes from the typical to the anomalous. In the radon data used to illustrate the techniques, the paired time-series typically neither correlate nor cohere but do so anomalously for short periods. In other data, the emphasis might be different, e.g. the time series might typically both correlate and cohere but contain anomalous periods where they do not or, the time-series might typically cohere at some frequencies but contain anomalous periods where the cohering frequencies change.

Correlation does not imply causality, is not proof of causality: at most, correlation might be evidence to support causality. In the dataset analysed above, despite the clear temporal correspondence of the late September and late August time-domain anomalies to earthquakes, and the temporal correspondence of the mid-late November less well-defined time-domain anomaly to another earthquake, this is all that is shown, i.e. temporal correspondence. The analysis does not prove that the anomalies are related to the earthquakes, i.e. does not demonstrate that an earthquake-stimulus radon-response relationship exists, but such analysis does provide necessary evidence towards the demonstration that such a relationship might exist.

With regard to magnitude anomalies, care must be taken to apply criteria used for identifying anomalies correctly dependent upon the probability distribution(s) of the data being investigated. Noting the simplicity and familiarity of the normal distribution, and associated *de facto* standard criteria for determining anomalies, a technique such as the SRI which maps data onto standard normal variables is useful, but this technique is also useful in effectively equalising different, generally non-linear radon-emission characteristics and facilitating comparison in terms of probability of occurrence.
