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Learn to distinguish between beneficial and harmful control variables in statistical models through this lecture that explores when adding variables improves causal inference versus when it introduces bias, covering concepts like colliders, mediators, and confounders with practical examples to help you make better decisions about which variables to include or exclude in your statistical analyses.
