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Exploratory Data Analysis. Wiley Series in Computational Statistics

  • Book

  • 448 Pages
  • October 2018
  • John Wiley and Sons Ltd
  • ID: 3187501
This book can be used by a wide group of users of statistics. It emphasizes the principles, fundamental concepts, and procedures of exploratory data analysis. Readers learn to recognize situations where procedures can and should be used. Statistical concepts based on models particularly tests and confidence intervals are also included. Both new and familiar data analysis problems are explored throughout with the aim of producing a fresh approach to teaching a serious course in statistics. Emphasis is placed on general principles, rather than narrow interpretations. For the technically challenged, concluding chapters on the treatment of large data sets and high–dimensional problems are also included. An author website that contains additional material (such as MCMC and Bayesian computing), content hints, selected solutions to exercises, and software routines in R, S–Plus, SPSS, SAS, and BUGS is freely available.

Authors

Dhammika Amaratunga Javier Cabrera Luisa T. Fernholz Stephan Morgenthaler