Statistics of Earth Science Data

Statistics of Earth Science Data PDF

Author: Graham J. Borradaile

Publisher: Springer Science & Business Media

Published: 2013-11-11

Total Pages: 371

ISBN-13: 3662052237

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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)

Introduction to Python in Earth Science Data Analysis

Introduction to Python in Earth Science Data Analysis PDF

Author: Maurizio Petrelli

Publisher: Springer Nature

Published: 2021-09-16

Total Pages: 229

ISBN-13: 3030780554

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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.

Statistics for Earth and Environmental Scientists

Statistics for Earth and Environmental Scientists PDF

Author: John H. Schuenemeyer

Publisher: John Wiley & Sons

Published: 2011-04-12

Total Pages: 341

ISBN-13: 1118102215

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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.

Statistics for Earth and Environmental Scientists

Statistics for Earth and Environmental Scientists PDF

Author: Jacek Fabian

Publisher:

Published: 2016-08-01

Total Pages: 290

ISBN-13: 9781681175713

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Earth scientists are often involved in taking observations on the earth's surface and its interior. Earth scientists are confronted with many challenges. Phenomena of interest are often deep within the earth surface, in oceans, or in the atmosphere. Collecting data often is costly, time consuming, and hampered by limited access. Geologic events occur at irregular intervals, often widely spaced. Decisions made on the basis of studies in the earth sciences can have significant long term consequences. An understanding of data used in decision making is critical. Exploratory data analysis provides insight into data quality, variability, and structure. Constructing models provides a basis for understanding complex geologic processes and for making inferences. Since earth scientists depend largely on observations, particularly on observations where there is a large portion of uncertainty, Statistics plays a major role in drawing inferences concerning the earth and its interior.Statistics for Earth and Environmental Scientists provides comprehensive theoretical and practical knowledge of statistical applications for solving real-world environmental problems. This book is envisioned for students and practitioners of the earth and environmental sciences who want to practise statistical tools to unravel real problems. It offers a variety of tools that are used across earth science disciplines. Statistical methods need to be understood because today's interesting problems are complex and include uncertainty. These complex problems take account of energy resources, climate change, and geologic hazards.

Statistics and Data Analysis in Geology

Statistics and Data Analysis in Geology PDF

Author: John C. Davis

Publisher: John Wiley & Sons

Published: 1973

Total Pages: 584

ISBN-13:

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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

Integrating Data Science and Earth Science PDF

Author: Laurens M. Bouwer

Publisher: Springer Nature

Published: 2022-07-14

Total Pages: 158

ISBN-13: 3030995461

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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.

MATLAB® Recipes for Earth Sciences

MATLAB® Recipes for Earth Sciences PDF

Author: Martin H. Trauth

Publisher: Springer Science & Business Media

Published: 2007

Total Pages: 294

ISBN-13: 3540727485

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Introduces methods of data analysis in geosciences using MATLAB such as basic statistics for univariate, bivariate and multivariate datasets, jackknife and bootstrap resampling schemes, processing of digital elevation models, gridding and contouring, geostatistics and kriging, processing and georeferencing of satellite images, digitizing from the screen, linear and nonlinear time-series analysis and the application of linear time-invariant and adaptive filters. Includes a brief description of each method and numerous examples demonstrating how MATLAB can be used on data sets from earth sciences.

Practical Statistics for Geographers and Earth Scientists

Practical Statistics for Geographers and Earth Scientists PDF

Author: Nigel Walford

Publisher: John Wiley & Sons

Published: 2011-07-05

Total Pages: 385

ISBN-13: 1119957028

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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

Use and Abuse of Statistical Methods in the Earth Sciences

Use and Abuse of Statistical Methods in the Earth Sciences PDF

Author: William B. Size

Publisher: Oxford University Press, USA

Published: 1987

Total Pages: 200

ISBN-13:

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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.