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.
A small working example.
Imagine reading activity and new article publication rising together. A pattern suggests a question, but it does not by itself establish the direction of influence.
A note to keep beside it.
A column name can hide an assumption. Check units, missing values, and the counting rule before combining observations that only appear to be alike.
- Separate association from a causal claim.
- Consider shared influences and selection.
- Ask what evidence would distinguish explanations.
Follow a related question
Separate essential work from optional features.
A service that fails with contextCompare one object under two light sources.
A color depends on the lightKeep learning
Related background to continue exploring this subject.
NIST: statistical engineering NIST: the International System of Units