Box and whisker plots are useful for visualizing data distribution and identifying outliers, making them ideal for data exploration. They are particularly effective when dealing with heteroskedastic data, as they can highlight variations in data spread. The main difference between box plots and other statistical methods lies in their ability to summarize data through quartiles and visualize the median, which is not always evident in other graphical representations. While not commonly used in published work, they provide valuable insights during preliminary data analysis. Overall, box and whisker plots serve as a powerful tool for understanding data characteristics.
