Statistical Data Analysis Explained

Few books on statistical data analysis in the natural sciences are
written at a level that a non-statistician will easily understand.
This is a book written in colloquial language, avoiding
mathematical formulae as much as possible, trying to explain
statistical methods using examples and graphics instead. To
use the book efficiently, readers should have some computer
experience. The book starts with the simplest of statistical
concepts and carries readers forward to a deeper and more extensive
understanding of the use of statistics in environmental sciences.
The book concerns the application of statistical and other computer
methods to the management, analysis and display of spatial data.
These data are characterised by including locations (geographic
coordinates), which leads to the necessity of using maps to display
the data and the results of the statistical methods. Although the
book uses examples from applied geochemistry, and a large
geochemical survey in particular, the principles and ideas equally
well apply to other natural sciences, e.g., environmental sciences,
pedology, hydrology, geography, forestry, ecology, and health
sciences/epidemiology.

The book is unique because it supplies direct access to software
solutions (based on R, the Open Source version of the S-language
for statistics) for applied environmental statistics. For all
graphics and tables presented in the book, the R-scripts are
provided in the form of executable R-scripts. In addition, a
graphical user interface for R, called DAS+R, was developed for
convenient, fast and interactive data analysis.

Statistical Data Analysis Explained: Applied Environmental
Statistics with R provides, on an accompanying website, the
software to undertake all the procedures discussed, and the data
employed for their description in the book.

Auteur

Clemens Reiman (born 1952) holds an M.Sc. in Mineralogy and
Petrology from the University of Hamburg (Germany), a Ph.D. in
Geosciences from Leoben Mining University, Austria, and a D.Sc. in
Applied Geochemistry from the same university. he has worked as a
lecturer in Mineralogy and Petrology and Environmental Sciences at
Leoben Mining University, as an exploration geochemist in eastern
Canada, in contract research in environmental sciences in Austria
and managed the laboratory of an Austrian cement company before
joining the Geological Survey of Norway in 1991 as a senior
geochemist. From March to October 2004 he was director and
professor at the German Federal Environment Agency
(Unweltbundesamt, UBAS), responsible for the Division II,
Environmental Health and Protection of Ecosystems. At present he is
chairman of the EuroGeoSurveys geochemistry expert group, acting
vice president of the International Association of GeoChemistry
(IAGC), and associate editor of both Applied Geochemistry and
Geochemistry: Exploration, Environment, Analysis.

Peter Filzmoser (born 1968) studies Applied Mathematics
at the Vienna University of Technology, Austria, where he also
wrote his doctoral thesis and habilitation devoted to the field of
multivariate statistics. His research led him to the area of robust
statistics, resulting in many international collaborations and
various scientific papers in this area. His interest in
applications of robust methods resulted in the development of R
software packages. He was and is involved in the Organisation of
several scientific evens devoted to robust statistics. Since 2001
he has been dozent at the Statistics Department at Vienna
University of Technology. He was visiting professor at the
universities of Vienna, Toulouse and Minsk.

Robert G. Garrett (Bob Garrett) studied Mining Geology
and Applied Geochemistry at Imperial College, London, and joined
the Geological Survey of Canada (GSC) in 1967 following
post-doctoral studies at Northwestern University, Evanston. For the
next 25 years his activities focused on regional geochemical
mapping in Canada, and overseas for the Canadian International
Development Agency, to support mineral exploration and resource
appraisal. Throughout his work there has been a use of computers
and statistics to manage data, assess their quality, and maximise
the knowledge extracted from them. In the 1990s he commenced
collaboration crops. Since then he has been involved in various
Canadian Federal and university-based research initiatives aimed at
providing sound science to support Canadian regulatory and
international policy activities concerning risk assessments and
risk management for metals. he retired in March 2005 but remains
active as an Emeritus Scientist.

Rudolf Dutter is senior statistician and full professor
at Vienna University of Technology, Austria. he studies Applied
Mathematics in Vienna (M.Sc.) and Statistics at Universite de
Montreal, Canada (Ph.D.). He spent three years as a post-doctoral
fellow at ETH, Zurich, working on computational robust statistics.
research and teaching activities followed at the Graz University of
Technology, and as a full professor of statistics at Vienna
University of Technology, both in Austria. he also taught and
consulted at Leoben Mining University, Technology, both in Austria.
he also taught and consulted at Leoben Mining University, Austria;
currently he consults in many fields of applied statistics with
main interests in computational and robust statistics, development
of statistical software, and geostatistics. He is author and
coauthor of many publications and several books, e.g., an early
booklet in German on geostatistics.

Résumé
Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand. This is a book written in colloquial language, avoiding mathematical formulae as much as possible, trying to explain statistical methods using examples and graphics instead. To use the book efficiently, readers should have some computer experience. The book starts with the simplest of statistical concepts and carries readers forward to a deeper and more extensive understanding of the use of statistics in environmental sciences. The book concerns the application of statistical and other computer methods to the management, analysis and display of spatial data. These data are characterised by including locations (geographic coordinates), which leads to the necessity of using maps to display the data and the results of the statistical methods. Although the book uses examples from applied geochemistry, and a large geochemical survey in particular, the principles and ideas equally well apply to other natural sciences, e.g., environmental sciences, pedology, hydrology, geography, forestry, ecology, and health sciences/epidemiology. The book is unique because it supplies direct access to software solutions (based on R, the Open Source version of the S-language for statistics) for applied environmental statistics. For all graphics and tables presented in the book, the R-scripts are provided in the form of executable R-scripts. In addition, a graphical user interface for R, called DAS+R, was developed for convenient, fast and interactive data analysis.

Statistical Data Analysis Explained: Applied Environmental Statistics with R provides, on an accompanying website, the software to undertake all the procedures discussed, and the data employed for their description in the book.

Contenu

Preface xiii

Acknowledgements xv

About the authors xvii

1 Introduction 1

1.1 The Kola Ecogeochemistry Project 5

1.1.1 Short description of the Kola Project survey area 6

1.1.2 Sampling and characteristics of the different sample materials 9

1.1.3 Sample preparation and chemical analy…