Distinguishing correlation from causation
Chapter 41 of the CLEP American Government study guide on Effortless Math covers Distinguishing correlation from causation: the key terms, the core ideas, and worked examples showing how this topic is tested on the exam.
CLEP American Government, Chapter 41
Distinguishing correlation from causation
Correlation means that two variables vary together. A positive association means higher values of one tend to accompany higher values of the other; a negative association means higher values accompany lower values. Direction is different from strength. Evidence display 41D plots counties, separates two regions, and marks an unusual county with a diamond. The main cloud trends upward, but the regional clusters occupy different levels and the outlier can pull a one-number summary away from the pattern followed by most counties.
The display supports description, not a causal arrow. Campaign history, industry, region, candidate strategy, or another factor could shape both variables. Candidate B's county vote share also does not reveal which residents supplied those ballots; that inference would require individual-level evidence.
A causal question asks what would have happened to the same units under a different condition.
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