Nonparametric statistical methods are used when traditional methods might not work. The article reviews tests and techniques that don't rely on specific assumptions about data distributions. They explore ways to analyze data without needing to know the exact shape of the data. The researchers also discuss how to estimate errors and confidence levels without making strict assumptions. The methods are demonstrated using real-world data from the Pisa study in 2019.