Level set trees provide a tool for analyzing multivariate functions. Level set trees are particularly efficient in visualizing and presenting properties related to local maxima and local minima of functions. Level set trees can help statistical inference related to estimating probability density functions and regression functions, and they can be used in cluster analysis and function optimization, among other things. Level set trees open a new way to look at multivariate functions, which makes the detection and analysis of multivariate phenomena feasible, going beyond one‐ and two‐dimensional analysis.This article is categorized under: Statistical and Graphical Methods of Data Analysis > Analysis of High Dimensional Data Statistical and Graphical Methods of Data Analysis > Statistical Graphics and Visualization Statistical and Graphical Methods of Data Analysis > Nonparametric Methods