Description
| Product ID: | 9783319553351 |
| Product Form: | Hardback |
| Country of Manufacture: | CH |
| Series: | Statistics and Computing |
| Title: | Basic Elements of Computational Statistics |
| Authors: | Author: Ostap Okhrin, Yarema Okhrin, Wolfgang Karl Hardle |
| Page Count: | 305 |
| Subjects: | Research methods: general, Research methods: general, Social research and statistics, Mathematical and statistical software, Maths for computer scientists, Social research & statistics, Mathematical & statistical software, Maths for computer scientists |
| Description: | Select Guide Rating This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R. This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R. It covers mathematical, statistical as well as programming problems in computational statistics and contains a wide variety of practical examples. In addition to the numerous R sniplets presented in the text, all computer programs (quantlets) and data sets to the book are available on GitHub and referred to in the book. This enables the reader to fully reproduce as well as modify and adjust all examples to their needs. The book is intended for advanced undergraduate and first-year graduate students as well as for data analysts new to the job who would like a tour of the various statistical tools in a data analysis workshop. The experienced reader with a good knowledge of statistics and programming might skip some sections on univariate models and enjoy the various ma thematical roots of multivariate techniques.The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book. |
| Imprint Name: | Springer International Publishing AG |
| Publisher Name: | Springer International Publishing AG |
| Country of Publication: | GB |
| Publishing Date: | 2017-10-10 |
