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

MAP20180018671

An Introduction to statistical learning : with applications in R / Gareth James...[et al.]. — Corrected at 8th. printing 2017. — New York [etc.] : Springer , 2017

440 p.

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 book

ISBN 978-1-4614-7137-0

ISBN 978-1-4614-7138-7 (eBook)

1. Modelos estadísticos . 2. Modelos econométricos . 3. Estadística de muestreo . 4. Muestreos . 5. Tablas estadísticas . 6. Ejercicios . I. James, Gareth . II. Springer . III. Título.