I am not a statistician and hope someone can point me towards the right direction. I have some time series data grouped into three classes like this:
Time Period 1 Time Period 2 Time Period 3
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[1,2,3,4,5,6...] [12,13,14,15] [17,3,1,3,4...]
[1,3,5,6,8,9...] [6,8,7,9,6,4] [1,2,5,7,3,2...]
[9,8,9,9,8,9...] [3,1,1,2,1,2] [7,8,9,9,9,8...]
The dots indicate that I have significantly more values for Time Period 1 and Time Period 3 than for Time Period 2. I am trying to define events of "interest". Interest is when there is a significant change in the transitions from Time Period 1 to Time Period 2 and Time Period 2 to Time Period 3. Of course, there could be a knob for determining what I mean for significant.
What I am looking for is a good metric that tells me if an event is of potential interest. Obviously, average would not do good due to outliers so all I could think of was the median which seemed like a good one i.e. if there is a significant change in the median from Time Period 1 to Time Period 2, then this transition is of interest.
While this metric is working out for me, I am curious if there is a more structured/formal approach to deriving a metric that is better than the median. As of now, the problem formulation is open as well so any suggestions/constructive criticisms are greatly appreciated.