Supervised statistical learning techniques have been developed over the time in very diverse lines of research and in a great variety of problems applied. These methods are mainly used in order to predict its response. to new data in complex problems due to its great flexibility compared to the classic models. However, many of these methods are called black box methods.because the relationships that are generated between the variables in the functions are not clear dear. In this sense, interpretable statistical learning has become an area of Very active research in recent years. The purpose of this document is to describe some of the most used techniques of interpretable statistical learning. With the In order to understand in greater depth the proposed techniques, an application with data on the offer price of real estate in Montevideo. several apply supervised statistical regression models to predict their price and are calculate some interpretability measures for them that allow to analyze the effect of a set of explanatory variables in the price of the property

Esta es una preimpresión del Número 1 del Vol 22 de la Revista Serie Documentos de Trabajo Universidad de la República. Facultad de Ciencias Económicas y de Administración, Instituto de Estadı́stica (IESTA) (This is a preprint for Issue 1 of Vol 22 of the Journal Serie Documentos de Trabajo Universidad de la República.Facultad de Ciencias Económicas y de Administración, Instituto de Estadı́stica (IESTA))