What is required to determine whether a finding is an anomaly or outlier? performing what-if analysis performing descriptive analytics

To determine whether a finding is an anomaly or outlier, performing **descriptive analytics** is typically required. Descriptive analytics involves summarizing and analyzing historical data to identify patterns, trends, and deviations from the norm. This can include statistical measures such as mean, median, standard deviation, and visualizations like histograms or box plots, which help in identifying data points that significantly differ from the rest of the dataset. **What-if analysis**, on the other hand, is more focused on exploring the potential outcomes of different scenarios or decisions based on varying inputs. While it can be useful in understanding the implications of changes in data, it is not primarily aimed at identifying anomalies or outliers. In summary, to identify anomalies or outliers, descriptive analytics is the more relevant approach.