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Special Features: · Offers a comprehensive treatment of statistics in geology.· Topics progress from background information to analysis of geological sequences, then maps, and finally multivariate observations.· The book places special emphasis on probability and statistics, including nonparametric statistics, constant-sum data, eigenvalue calculations, analysis of directional data, mapping and geostatistics, fractals, and multivariate analysis.· The text now includes numerous geological data sets that illustrate how specific computational procedures can be applied to problems in the Earth sciences. All data sets are available on the book's companion Web site.· Each chapter now ends with a set of exercises of greater or lesser complexity that the student can address using methods discussed in the chapter.· Provides expanded coverage of elementary probability theory.· The discussion of nonparametric methods has been expanded to address closure effects.· Coverage of eigenvalues and eigenvectors has been revised.· Includes a new section on singular value decomposition and the relationship between R- and Q-mode factor methods in the chapter on multivariate analysis.· The section on contour mapping has been revised to reflect modern practices.· Includes revised coverage of the many varieties of kriging and provides of series of simple demonstrations that illustrate how geostatistical methodologies work.· Includes a discussion of fractals, a promising area of future research.· The section on regression has been expanded to include several variants that have special significance in the Earth sciences.
Data on water quality and other environmental issues are being collected at an ever-increasing rate. In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources.The last fifteen years have seen major advances in the fields of exploratory data analysis (EDA) and robust statistical methods. The 'real-life' characteristics of environmental data tend to drive analysis towards the use of these methods. These advances are presented in a practical and relevant format. Alternate methods are compared, highlighting the strengths and weaknesses of each as applied to environmental data. Techniques for trend analysis and dealing with water below the detection limit are topics covered, which are of great interest to consultants in water-quality and hydrology, scientists in state, provincial and federal water resources, and geological survey agencies.The practising water resources scientist will find the worked examples using actual field data from case studies of environmental problems, of real value. Exercises at the end of each chapter enable the mechanics of the methodological process to be fully understood, with data sets included on diskette for easy use. The result is a book that is both up-to-date and immediately relevant to ongoing work in the environmental and water sciences.
Since Karl Pearson wrote his paper on spurious correlation in 1897, a lot has been said about the statistical analysis of compositional data, mainly by geologists such as Felix Chayes. The solution appeared in the 1980s, when John Aitchison proposed to use Iogratios. Since then, the approach has seen a great expansion, mainly building on the idea of the `natural geometry' of the sample space. Statistics is expected to give sense to our perception of the natural scale of the data, and this is made possible for compositional data using Iogratios. This publication will be a milestone in this process.
Unlike most other sciences, geology does not have a strong tradition of numerical analysis. It is, however, increasingly common for primary geological information to be quantitative rather than descriptive, and analysis of numerical data is now a skill of immense value to any earth scientist. The authors of this book have set out to provide students at undergraduate and graduate level with a thorough grounding in the statistical techniques required in the earth sciences. All the modern statistical methods employed by geologists and geophysicists are covered, with clear worked examples using the type of data the reader is likely to encounter.
This thoroughly revised edition presents important methods in the quantitative analysis of geologic data. Retains the basic arrangement of the previous edition but expands sections on probability, nonparametric statistics, and Fourier analysis. Contains revised coverage of eigenvalues and eigenvectors, and new coverage of data analysis methods, such as the semivariogram and the process of kriging.
Presents nearly all the important elementary and analytical methods of statistics, designed for the needs of the geoscientist and completely free from higher mathematics. Translated from the second German edition.
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.