What is the Look Elsewhere Effect?
The look elsewhere effect is a cognitive bias that occurs when people find seemingly significant patterns or results in data by chance, due to the large number of comparisons or tests performed. In other words, when researchers or individuals search through multiple sources of data or perform multiple statistical tests, they are more likely to find at least one “significant” result simply by chance, even if there is no true effect or relationship. This can lead to false positives, overinterpretation of data, and the reporting of spurious findings. To counteract the look elsewhere effect, researchers often use statistical methods, such as Bonferroni correction, to control for multiple comparisons and reduce the likelihood of identifying false positives.
Examples of the Look Elsewhere Effect
In scientific research, the look elsewhere effect can lead to the publication of studies with false positive results, especially when multiple hypotheses are tested without proper statistical corrections. This can contribute to the replication crisis, where published findings cannot be reliably reproduced by other researchers.
Data mining involves searching through large datasets to identify patterns and relationships. The look elsewhere effect can occur when data miners test multiple variables or relationships without accounting for the increased likelihood of finding false positives, leading to erroneous conclusions or predictions.
In medical diagnostics, the look elsewhere effect can lead to false positive results when multiple tests are conducted on a patient without considering the increased probability of chance findings. This can result in unnecessary treatments or interventions.
Traders and investors who perform multiple analyses on financial data may experience the look elsewhere effect, leading to the identification of spurious patterns or trends. This can result in poor investment decisions based on chance findings rather than true market trends.