The ________ method in data quality assessment identifies data values that fall outside the expected range of values.

  • Data aggregation
  • Data sampling
  • Outlier detection
  • Pattern recognition
Outlier detection is a method used in data quality assessment to identify data values that deviate significantly from the expected range or distribution of values within a dataset. Outliers can indicate errors, anomalies, or valuable insights in the data and are important to identify and address for accurate analysis and decision-making.
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