E-Book Overview
This is a very gentle book. It provides a first look at things like HTML, XML, SQL and other supposedly arcane technologies used in data storage, retrieval and manipulation. Coming from Paul Murrell, it has a delicately humorous, slightly quirky slant in some of the examples he chooses, but maintaining full relevance. There is a little bit on R included, but almost as an afterthought. It is not a book abour R. The book is clearly intended to be a teaching resource for a component of a modern statistics subject, probably at second or (honours) first year. I found the pace a little slow, but then, I'm no longer a student! The entire text of the book has been released electronically and, in the spirit of R itself, is free. You just can't sell it. So classes using the text could be expected to have their own electronic materials. A search on something like "Paul Murrell Data Technonogies" should locate it quickly enough.
E-Book Content
IntroductIon to
data
technologIes
Chapman & Hall/CRC
Computer Science and Data Analysis Series The interface between the computer and statistical sciences is increasing, as each discipline seeks to harness the power and resources of the other. This series aims to foster the integration between the computer sciences and statistical, numerical, and probabilistic methods by publishing a broad range of reference works, textbooks, and handbooks. SERIES EDITORS David Blei, Princeton University David Madigan, Rutgers University Marina Meila, University of Washington Fionn Murtagh, Royal Holloway, University of London Proposals for the series should be sent directly to one of the series editors above, or submitted to: Chapman & Hall/CRC 4th Floor, Albert House 1-4 Singer Street London EC2A 4BQ UK
Published Titles Bayesian Artificial Intelligence Kevin B. Korb and Ann E. Nicholson
Design and Modeling for Computer Experiments
Computational Statistics Handbook with MATLAB®, Second Edition
Kai-Tai Fang, Runze Li, and Agus Sudjianto
Wendy L. Martinez and
Paul Murrell
Angel R. Martinez Pattern Recognition Algorithms for Data Mining Sankar K. Pal and Pabitra Mitra
Introduction to Data Technologies Introduction to Machine Learning and Bioinformatics Sushmita Mitra, Sujay Datta, Theodore Perkins, and George Michailidis
Exploratory Data Analysis with MATLAB®
R Graphics
Wendy L. Martinez and Angel R. Martinez
Paul Murrell
Clustering for Data Mining:
R Programming for Bioinformatics
A Data Recovery Approach
Robert Gentleman
Boris Mirkin
Semisupervised Learning for
Correspondence Analysis and Data
Computational Linguistics
Coding with Java and R Fionn Murtagh
Steven Abney Statistical Computing with R Maria L. Rizzo
IntroductIon to
data
technologIes Paul Murrell
This work is licensed under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 New Zealand License. To view a copy of this license, visit: http://creativecommons.org/licenses/bync-sa/3.0/nz/ or send a letter to: Creative Commons, 171 Second Street, Suite 300, San Francisco, California, 94105, USA.
Chapman & Hall/CRC Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2009 by Paul Murrell Chapman & Hall/CRC is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number-13: 978-1-4200-6517-6 (Hardcover) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publ