Two quantities may rise and fall together. That association can be useful, but it does not by itself show that changing one will change the other.
Consider shared influences, the order of events, and how the observations were selected. A third factor may affect both quantities. A pattern that appears in a selected group can also differ from the pattern in a wider population.
Use the relationship to frame a more specific investigation. State which explanations remain possible and what additional evidence would help distinguish them. A clear association is a beginning for causal questions, rather than a complete answer to them.
Picture this situation.
Consider two daily counts increasing during the same event. Their movement may reflect a shared condition rather than one count causing the other.
A second way to look.
Look for the comparison behind the visual impression. The baseline, time window, and group definition can change what a pattern seems to mean.
- Separate association from a causal claim.
- Consider shared influences and selection.
- Ask what evidence would distinguish explanations.
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NIST: statistical engineering NIST: the International System of Units
