Why it matters
Co-movement can help describe data and generate hypotheses. It cannot on its own tell us which intervention would change an outcome.
A worked example
Hotter days can bring both more ice-cream sales and more swimming. Their association need not mean ice cream causes swimming.
Illustrative example · simplified assumptionsA common mistake
Treating an association as a causal mechanism.
Where the idea needs care
Common causes, reverse causation and selection can generate associations. A weak linear correlation can also hide a nonlinear relationship.
Apply the idea
Explain this concept using a different example from your spending, work, business or a policy debate. State what stays fixed and what could change the result.
See the supporting infographic

The written explanation above is the main lesson. This image offers another way to remember it.
Sources and further study
Examples and explanations by Alibomics. Numeric illustrations are not current market quotations.
