Nonparametric statistics, a branch of statistics that doesn't rely on specific assumptions about data, offers precise methods for analyzing information. These methods are versatile, requiring only basic assumptions about the data's source. They provide exact results for hypothesis tests, confidence intervals, and more. Nonparametric techniques are efficient and robust, meaning they work well even with unusual data points or deviations from the norm. In particular, rank-based nonparametric methods are useful for comparing data from different groups. These methods have been around for a long time and are still widely used today for analyzing data effectively.