Correlation Pitfalls, Spurious Associations & Causality

Build disciplined interpretations of correlations in observational data. Explore common causes, reverse direction, shared time trends, selection, restricted ranges, nonlinear relationships and ecological inference. Prerequisites: scatter plots and Pearson and rank correlation. Original scenarios move from recognizing a plausible alternative explanation to evaluating study designs and the scope of intervention claims. Worked solutions explain why tempting conclusions exceed the evidence.

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