What are you seeing?It is the memory of the case: what happened, when it happened, and what you observed at each moment.
Why it mattersWithout memory, it is easy to believe something worked just because you saw it once and never compared again.
How to think about itStart with the big picture: check the date/time first, then the specific observation for that moment.
Very simple exampleA photo from today shows how the plant is today; several observations ordered over time show whether it truly changed.
What are you seeing?The time series makes it possible to compare baseline state, intervention or event, latency, trend, and possible confounding factors.
Why it mattersConnecting these signals prevents concluding that something "worked" from a single isolated observation, without a prior comparison.
How to think about itCheck date/time, observation, comparison with the previous one, and the data's origin — not just the most recent data point.
Very simple exampleA visible improvement right after a change can be due to another factor (a confounder) that happened at the same time, not the change itself.
What are you seeing?The advanced reading distinguishes baseline state from intervention, and separates a real trend from noise or one-off coincidence.
Why it mattersA conclusion about "what worked" must be traceable to a complete time series, not to a single data point.
How to think about itDistinguish variable, mechanism, interaction, uncertainty, limitation, and what possible confounder could explain the same change.
Very simple exampleThe latency between an intervention and its visible effect can be days — judging "too soon" can lead to a false conclusion.