With "tools" I meant statistical tools, aka statistical tests. Because the log is a time series where events happen at random times, the typical tests like the

With "tools" I meant statistical tools, aka statistical tests. Because the log is a time series where events happen at random times, the typical tests like the t-test are not readily applicable. One way I am currently generating p-values is to look at questions like "When I did X / did not do X - how often did Y happen within the next 24 hours?". And put those numbers into statistical tests like the t-test. But since "Y" often is not just something that happened but something that has a value (For example "High energy / normal energy / a little tired / very tired") this discards some data. This and many other specifics in a random-interval-event-log probably allow for better tests than I came up with so far.