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Every subgroup in this dataset shows the same negative relationship between X and Y — yet pool all the points together and the trend can flip to positive. This is Simpson's Paradox, a real and reproducible statistical phenomenon caused by a confounding variable that drifts together with both the predictor and the group label. The simulator generates several subgroups of synthetic data, fits a genuine least-squares regression line to each one individually and to the pooled dataset, and renders both in 3D so you can watch the local trend disagree with the global one as you turn up the confound strength.