Principles of Data Science
Bias refers to a systematic error that leads to an incorrect understanding or interpretation of data, often skewing results in a specific direction. It can arise from various sources such as data collection methods, model assumptions, or even the data itself, leading to misleading conclusions. Understanding bias is crucial for ensuring accurate predictions, fair outcomes, and ethical considerations in data analysis.
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