Identifying and evaluating outliers

Discussion Questions
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Discussion Questions
Identifying and evaluating outliers is an essential aspect that warrants proper control, validation, and monitoring of data. Outliers can be evaluated using visual outlier detection methods using normal curves, box plots, charts. Another method to evaluate outliers is by using the parametric outlier detection method. This can use that standard deviation for a normal distribution, discordance outlier test, and Grubbs outlier test (Durivage, 2018).
Data integrity is essential for quality control as well as handling of OOS results because poor practices cause substandard products. There is a need for data managers to be proactive in ensuring data integrity is observed. There is a need to undertake regular audits to identify potential issues with risks. In this regard, outliers are important in highlighting the discrepancies existing within a particular data set. A simple audit of the electronic data system wi...