Outliers are crucial in epidemiological studies for several reasons:
Identifying Errors: They can reveal errors in data collection, entry, or processing that need correction. Detecting Novel Phenomena: Outliers may indicate new or rare events, such as the emergence of a new infectious disease or an unexpected response to a treatment. Assessing Data Quality: The presence and frequency of outliers can help assess the reliability and quality of the data being analyzed.
