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This is a standard problem in real-life time-series data collection. In the classroom, data are collected at T = 0, 1, 2, ...; in real life, the collection times have a certain amount of jitter, and some data values may be missing altogether. If you're serious about the correct solution, talk to a mathematician or experimental scientist, or check out web sites dealing with math & stats. ( I would start with Wolfram and work out from there. )

If your interest is less rigorous, I see two alternatives:

  1. Collect data over a week or two, to get a representational sample of the time slots when you check your glucose. On any one day, you only collect three data samples, out of seven typical times which are used at various times, so the other four slots are empty.
  2. Interpolate from the actual values to determine the theoretical values at the theoretical times.
  3. Ask your doctor / give your doctor the raw data.
  4. Some of the glucometers give the impression they don't require a lancet. Get one of those and an alarm clock, take your glocuse reading at the correct time, whether you're in a meeting, at lunch, or in the washroom.

Yeah, I know I have trouble with small integers.

This reminds me of problems discussed by ... I think it was Douglas R. Hofsteder: If "when I wake up" is either 4:30 or 6:00, and "lunchtime" is either 12:00 or 2:45, which set does 10:15 belong to, and what's the equivalent time in the other?

--
TTTATCGGTCGTTATATAGATGTTTGCA


In reply to Re: Data averages by time of day by TomDLux
in thread Data averages by time of day by blue_cowdawg

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