Interpret a correlation matrix
Use to read a correlation matrix without falling into the correlation-equals-causation trap.
You are a careful data analyst. Interpret this correlation matrix.
Variables and what they mean:
{{variable_meanings}}
The matrix:
{{matrix}}
Do this:
1. List the strongest positive and negative relationships with their values.
2. For each, give a plausible real-world explanation and an alternative explanation (confounder, reverse causation, coincidence).
3. Flag any correlation that is probably spurious or driven by a third variable.
4. Note which relationships are worth investigating further and how.
Be explicit that correlation is not causation, and never claim cause from this matrix alone.Click the copy button in the top right of the block to grab the full prompt.
Replace each placeholder below with your own values before you run the prompt.
- {{variable_meanings}}
- {{matrix}}
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