Book by Reimann Clemens Filzmoser Peter Garrett Robert Dut
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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.
Statistical Data Analysis Explained
Applied Environmental Statistics with R
Statistical Data Analysis Explained provides an accessible guide to practical data analysis for applied environmental sciences, using many of today's advanced Statistical. Written in a concise and logical manner, the book avoids complex Statistical jargon and can be easily understood by non-statisticians. Mathematical formulae is avoided where possible with explanations carried out using relevant examples.
Opening with the simplest of statistical concepts, the book carefully moves on to introduce the reader to a more comprehensive understanding of he use of statistics within the environmental sciences. Clearly structured throughout, the book links the application of Statistical and other computer methods to the management, analysis and presentation of spatial data.
Many of the examples used in the book are taken from applied geochemistry,although he principles and ideas apply equally to other natural sciences, for example, environmental science, hydrology, geography, forestry and ecology. The book will be an invaluable reference to anyone working with spatially-dependent data.
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