How Percentiles and the IQR Can Automatically Flag Bad Data Rows

Data analyst Michael Nocito published a practical guide on August 9, 2026, explaining how to use percentiles and the interquartile range to detect outliers in datasets. The method involves calculating the 25th and 75th percentiles, finding their difference, and setting a fence at 1.5 times that difference beyond the 75th percentile. Any data point exceeding that fence is flagged as a row worth investigating. Nocito demonstrates the technique on a 16-row order revenue dataset, where one mistyped quantity is automatically identified while legitimate large orders remain within bounds. The approach reduces the question of data quality to a single query that returns a specific list of suspect rows.