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Detection of Gross Error: The Q Test

Detection of Gross Error: The Q Test

When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...

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Related Experiment Video

Updated: Apr 30, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

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Published on: December 15, 2023

A Robust Artificial Intelligence Method for Detecting Near-Non-Reactive Non-Stress Test Patterns: What Should We

Haitian Chen¹, Caixia Zhu¹, Zhuyu Li¹

¹Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, Guangdong Provincial Clinical Research Center for Obstetrical and Gynecological Diseases, Guangzhou 510080, China.

Maternal-Fetal Medicine (Wolters Kluwer Health, Inc.)

|April 29, 2026

Summary

No abstract available in PubMed .

Keywords:

Artificial intelligence Fetal heart rate Non-stress test

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