Outliers and anomalies in data might indicate potential fraud, poor customer experience, or a low level of satisfaction. They might also indicate service gaps, network interruptions or data errors that should be addressed at an operational level.
Analysts must also identify and decide how to treat outliers and anomalies before developing predictive models using time series, classification, and parametric data analysis techniques. The free outlier and anomaly detection template is one of several box and whisker templates that allow users to identify, visualize and analyze outliers and anomalies posted in Box Plot Graph Outlier Data Analysis Templates.
Time series data analysts can also download a FREE CASE STUDY: Humber River Water Levels Time Series Box Plot Data Analysis. This case study is the result of data being run through a box and whisker time series algorithm. A summary of how these and other templates apply the theory of the box plot to analyze data can be found at Box Plot Outlier Data Analysis. A box plot graph analysis developer starter kit and outlier analysis resources can help any analyst get started coding custom box and whisker templates to suit their own analytical needs.