Data collection bias refers to systematic errors that occur during the gathering of data, leading to results that do not accurately reflect the true characteristics of the population being studied. This bias can arise from various sources, such as sampling methods, survey design, or participant selection. Understanding this bias is crucial for ensuring fairness and accuracy in big data analytics, as it can distort insights and lead to misleading conclusions.
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