Centro de Documentacion de Fundación MAPFRE - An Introduction to statistical learning : with applications in R

Edition: Corrected at 8th. printing 2017Publication: New York [etc.] : Springer , 2017Physical description: 440 p.Notes: Sumario: Statistical learning refers to a vast set of tools for understanding data.These tools can be classified as supervised or unsupervised. Broadly speaking, supervised statistical learning involves building a statistical model for predicting, or estimating, an output based on one or more inputs.Problems of this nature occur in fields as diverse as business, medicine, astrophysics, and public policy. With unsupervised statistical learning, there are inputs but no supervising output; nevertheless we can learn relationships and structure from such data. To provide an illustration of some applications of statistical learning, we briefly discuss three real-world data sets that are considered in this bookMateria / lugar / evento: Modelos estadísticos Modelos econométricos Estadística de muestreo Muestreos Tablas estadísticas Ejercicios Otros autores: James, Gareth
Springer
Other categories: 937.42Standard numbers: ISBN 978-1-4614-7137-0 ISBN 978-1-4614-7138-7 (eBook)