This article provides an introduction to the major types of nonparametric regression techniques, including kernel, spline and orthogonal projection methods. Practical aspects of the methods and their applicability in environmental statistics are emphasized through examples and discussion. Topics covered include bandwidth selection, nonparametric regression in multiple dimensions, and for data exhibiting correlated errors. Extensions to generalized regression models and semiparametic regression are also discussed.