I am working with a time series (discrete) that has ideally 1 value per time stamp. In some cases, we are seeing multiples that have a wide range all recorded with the same time stamp.
Up to now, we had been averaging the data but have found quite a few instances of very big ranges.
Should we instead be considering the modes (sometimes there are only 2 values), should we be considering a different method? When should we consider just throwing them out? There are many missing values in this data so using previous and following values in the sequence is not ideal.
I can't recall from my previous stats what the preferred method of dealing with these values is, as I haven't come across this in some time (maybe ever, in practice). Any ideas on how to handle the situation is greatly appreciated. Resources to look up would very much help as well!
Essentially the data sometimes looks like this, where the values are separated by ";" (these are not in sequence):
00:43:00 "78;66;81" 02:01:00 "68;74" 03:53:00 "78;86;88;95;95;111;102;97;94;95" 15:48:00 "81;120;97;58;84
While the ideal is to have 1 per timestamp, the reason why there is more than one in some instances is the truncation at minutes by the database. However, we need to pick just one value to represent that timestamp as we don't care about the seconds details.