10. What is bias in data and how does it affect models?
Bias in data occurs when certain groups, patterns, or outcomes are overrepresented or underrepresented. This leads models to learn distorted relationships. Biased data produces unfair, inaccurate, or unreliable predictions. In real systems, this affects trust, compliance, and business outcomes, so bias detection and correction are critical.

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