Several factors contribute to loss of detail, including:
Data Aggregation: Combining data from multiple sources or summarizing it can mask fine details. Sampling Bias: Non-representative samples can lead to generalizations that ignore important sub-group variations. Measurement Error: Inaccuracies in data collection tools or methods can distort details. Data Privacy Concerns: De-identification processes to protect personal health information can result in loss of valuable context.
