What is the term for a systematic error in statistics?

The term for a systematic error in statistics is bias. Bias refers to a consistent, predictable error that skews results in a particular direction, making the data less accurate. This can occur in various stages of data collection and analysis, such as sampling bias, measurement bias, or response bias. When bias is present, it means that the conclusions drawn from the data may not reflect the true population or phenomenon being studied, which can lead to misleading interpretations and poor decision-making.

Understanding bias is crucial for accurate statistical analysis, as it emphasizes the importance of ensuring objectivity and thoroughness in data collection methods. Addressing bias can significantly enhance the validity and reliability of research findings, ultimately contributing to better-informed conclusions and strategies in various applications, including finance and modeling.