Statistics Of Earth Science Data
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Statistics Of Earth Science Data
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Author : Graham J. Borradaile
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11
Statistics Of Earth Science Data written by Graham J. Borradaile and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Technology & Engineering categories.
From the reviews: "All in all, Graham Borradaile has written and interesting and idiosyncratic book on statistics for geoscientists that will be welcome among students, researchers, and practitioners dealing with orientation data. That should include engineering geologists who work with things like rock fracture orientation measurements or clast alignment in paleoseismic trenches. It won’t replace the collection of statistics and geostatistics texts in my library, but it will have a place among them and will likely be one of several references to which I turn when working with orientation data.... The text is easy to follow and illustrations are generally clear and easy to read..."(William C. Haneberg, Haneberg Geoscience)
Statistics For Earth And Environmental Scientists
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Author : John H. Schuenemeyer
language : en
Publisher: John Wiley & Sons
Release Date : 2011-04-12
Statistics For Earth And Environmental Scientists written by John H. Schuenemeyer and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-12 with Mathematics categories.
A comprehensive treatment of statistical applications for solving real-world environmental problems A host of complex problems face today's earth science community, such as evaluating the supply of remaining non-renewable energy resources, assessing the impact of people on the environment, understanding climate change, and managing the use of water. Proper collection and analysis of data using statistical techniques contributes significantly toward the solution of these problems. Statistics for Earth and Environmental Scientists presents important statistical concepts through data analytic tools and shows readers how to apply them to real-world problems. The authors present several different statistical approaches to the environmental sciences, including Bayesian and nonparametric methodologies. The book begins with an introduction to types of data, evaluation of data, modeling and estimation, random variation, and sampling—all of which are explored through case studies that use real data from earth science applications. Subsequent chapters focus on principles of modeling and the key methods and techniques for analyzing scientific data, including: Interval estimation and Methods for analyzinghypothesis testing of means time series data Spatial statistics Multivariate analysis Discrete distributions Experimental design Most statistical models are introduced by concept and application, given as equations, and then accompanied by heuristic justification rather than a formal proof. Data analysis, model building, and statistical inference are stressed throughout, and readers are encouraged to collect their own data to incorporate into the exercises at the end of each chapter. Most data sets, graphs, and analyses are computed using R, but can be worked with using any statistical computing software. A related website features additional data sets, answers to selected exercises, and R code for the book's examples. Statistics for Earth and Environmental Scientists is an excellent book for courses on quantitative methods in geology, geography, natural resources, and environmental sciences at the upper-undergraduate and graduate levels. It is also a valuable reference for earth scientists, geologists, hydrologists, and environmental statisticians who collect and analyze data in their everyday work.
Introduction To Python In Earth Science Data Analysis
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Author : Maurizio Petrelli
language : en
Publisher: Springer Nature
Release Date : 2021-09-16
Introduction To Python In Earth Science Data Analysis written by Maurizio Petrelli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-16 with Science categories.
This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.
Data Analysis In The Earth Sciences Using Matlab
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Author : Gerard V. Middleton
language : en
Publisher:
Release Date : 2000
Data Analysis In The Earth Sciences Using Matlab written by Gerard V. Middleton and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Earth sciences categories.
Exploring the application of MATLAB to the various earth sciences, this text presents an integrated, step-by-step introduction to data analysis and the use of MATLAB.
Use And Abuse Of Statistical Methods In The Earth Sciences
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Author : William B. Size
language : en
Publisher: Oxford University Press, USA
Release Date : 1987
Use And Abuse Of Statistical Methods In The Earth Sciences written by William B. Size and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Earth sciences categories.
A major goal of earth scientists is to make geological interpretations based on statistical inferences, but accomplishing this is difficult due to the "abuse" of statistical methods. This book, the first in the International Association for Mathematical Geology Series, addresses the underlying assumptions of randomness, normality, and variance of sample data used with statistical methods. The authors uncover the reasons for unreliable or invalid statistical results and discuss the use of statistical measures of association, correlation, and regressions with relatively uncontrolled and variable natural data. Their analyses help to bridge the gap between geostatisticians and earth science researchers, and will be valuable to a wide range of earth scientists.
Statistics And Data Analysis In Geology
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Author : John C. Davis
language : en
Publisher: John Wiley & Sons
Release Date : 1973
Statistics And Data Analysis In Geology written by John C. Davis and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with Science categories.
Thoroughly revised and updated, this new edition of the text that helped define the field continues to present important methods in the quantitative analysis of geologic data, while showing students how statistics and computing can be applied to commonly encountered problems in the earth sciences. In addition to new and expanded coverage of key topics, the Third Edition features new pedagogy, end-of-chapter review exercises, and an accompanying website that contains all of the data for every example and exercise found in the book.
Integrating Data Science And Earth Science
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Author : Laurens M. Bouwer
language : en
Publisher: Springer Nature
Release Date : 2022-07-14
Integrating Data Science And Earth Science written by Laurens M. Bouwer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-14 with Science categories.
This open access book presents the results of three years collaboration between earth scientists and data scientist, in developing and applying data science methods for scientific discovery. The book will be highly beneficial for other researchers at senior and graduate level, interested in applying visual data exploration, computational approaches and scientifc workflows.
Introduction To Geological Data Analysis
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Author : ARH Swan
language : en
Publisher: Wiley-Blackwell
Release Date : 1995-03-29
Introduction To Geological Data Analysis written by ARH Swan and has been published by Wiley-Blackwell this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-03-29 with Science categories.
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.
Practical Statistics For Geographers And Earth Scientists
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Author : Nigel Walford
language : en
Publisher: John Wiley & Sons
Release Date : 2011-07-05
Practical Statistics For Geographers And Earth Scientists written by Nigel Walford and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-05 with Science categories.
Practical Statistics for Geographers and Earth Scientists provides an introductory guide to the principles and application of statistical analysis in context. This book helps students to gain the level of competence in statistical procedures necessary for independent investigations, field-work and other projects. The aim is to explain statistical techniques using data relating to relevant geographical, geospatial, earth and environmental science examples, employing graphics as well as mathematical notation for maximum clarity. Advice is given on asking the appropriate preliminary research questions to ensure that the correct data is collected for the chosen statistical analysis method. The book offers a practical guide to making the transition from understanding principles of spatial and non-spatial statistical techniques to planning a series analyses and generating results using statistical and spreadsheet computer software. Learning outcomes included in each chapter International focus Explains the underlying mathematical basis of spatial and non-spatial statistics Provides an geographical, geospatial, earth and environmental science context for the use of statistical methods Written in an accessible, user-friendly style Datasets available on accompanying website at www.wiley.com/go/Walford
Overcoming Data Scarcity In Earth Science
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Author : Angela Gorgoglione
language : en
Publisher: MDPI
Release Date : 2020-05-22
Overcoming Data Scarcity In Earth Science written by Angela Gorgoglione and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-22 with Science categories.
heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable is difficult, mainly because of i) the high cost of the monitoring campaigns and ii) the low reliability of measurements (e.g., due to occurrences of equipment malfunctions and/or issues related to equipment location). The lack of a sufficient amount of Earth science data may induce an inadequate representation of the response’s complexity in any environmental system to any type of input/change, both natural and human-induced. In such a case, before undertaking expensive studies to gather and analyze additional data, it is reasonable to first understand what enhancement in estimates of system performance would result if all the available data could be well exploited. Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. Different approaches are available to deal with missing data. Traditional statistical data completion methods are used in different domains to deal with single and multiple imputation problems. More recently, machine learning techniques, such as clustering and classification, have been proposed to complete missing data. This book showcases the body of knowledge that is aimed at improving the capacity to exploit the available data to better represent, understand, predict, and manage the behavior of environmental systems at all practical scales.