Aggregation Bias

Aggregation bias occurs when data from different groups or categories are combined without accounting for their differences, leading to misleading conclusions. For example, averaging income levels across a diverse population might hide important variations within subgroups, such as age, education, or location. This bias can cause models or analyses to make inaccurate predictions or policies because they overlook the unique characteristics of individual groups. Essentially, aggregation bias results from treating diverse data as uniform, which can distort understanding and decision-making. Recognizing and addressing this bias helps ensure more accurate and fair insights.