Statistics For Geography And Environmental Science
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| Author | : Richard Harris |
| Publisher | : Routledge |
| Total Pages | : 280 |
| Release | : 2014-05-01 |
| Genre | : Science |
| ISBN | : 1317904400 |
Statistics are important tools for validating theory, making predictions and engaging in policy research. They help to provide informed commentary about social and environmental issues, and to make the case for change. Knowledge of statistics is therefore a necessary skill for any student of geography or environmental science. This textbook is aimed at students on a degree course taking a module in statistics for the first time. It focuses on analysing, exploring and making sense of data in areas of core interest to physical and human geographers, and to environmental scientists. It covers the subject in a broadly conventional way from descriptive statistics, through inferential statistics to relational statistics but does so with an emphasis on applied data analysis throughout.
| Author | : Miguel F. Acevedo |
| Publisher | : CRC Press |
| Total Pages | : 549 |
| Release | : 2012-12-07 |
| Genre | : Mathematics |
| ISBN | : 1466592214 |
Providing a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to implement data analysis methods using open-source software. Given the importance of interdisciplinary work in sustain
| Author | : Penny A. Cook |
| Publisher | : Routledge |
| Total Pages | : 218 |
| Release | : 2005-08-10 |
| Genre | : Science |
| ISBN | : 113463885X |
Using Statistics to Understand the Environment covers all the basic tests required for environmental practicals and projects and points the way to the more advanced techniques that may be needed in more complex research designs. Following an introduction to project design, the book covers methods to describe data, to examine differences between samples, and to identify relationships and associations between variables. Featuring: worked examples covering a wide range of environmental topics, drawings and icons, chapter summaries, a glossary of statistical terms and a further reading section, this book focuses on the needs of the researcher rather than on the mathematics behind the tests.
| Author | : John H. Schuenemeyer |
| Publisher | : John Wiley & Sons |
| Total Pages | : 341 |
| Release | : 2011-04-12 |
| Genre | : Mathematics |
| ISBN | : 1118102215 |
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.
| Author | : Nigel Walford |
| Publisher | : John Wiley & Sons |
| Total Pages | : 385 |
| Release | : 2011-07-05 |
| Genre | : Science |
| ISBN | : 1119957028 |
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
| Author | : Carsten Dormann |
| Publisher | : Springer Nature |
| Total Pages | : 264 |
| Release | : 2020-12-20 |
| Genre | : Medical |
| ISBN | : 3030550206 |
Environmental Data Analysis is an introductory statistics textbook for environmental science. It covers descriptive, inferential and predictive statistics, centred on the Generalized Linear Model. The key idea behind this book is to approach statistical analyses from the perspective of maximum likelihood, essentially treating most analyses as (multiple) regression problems. The reader will be introduced to statistical distributions early on, and will learn to deploy models suitable for the data at hand, which in environmental science are often not normally distributed. To make the initially steep learning curve more manageable, each statistical chapter is followed by a walk-through in a corresponding R-based how-to chapter, which reviews the theory and applies it to environmental data. In this way, a coherent and expandable foundation in parametric statistics is laid, which can be expanded in advanced courses.The content has been “field-tested” in several years of courses on statistics for Environmental Science, Geography and Forestry taught at the University of Freiburg.
| Author | : Danny McCarroll |
| Publisher | : CRC Press |
| Total Pages | : 497 |
| Release | : 2016-11-03 |
| Genre | : Mathematics |
| ISBN | : 1498758940 |
This book is aimed directly at students of geography, particularly those who lack confidence in manipulating numbers. The aim is not to teach the mathematics behind statistical tests, but to focus on the logic, so that students can choose the most appropriate tests, apply them in the most convenient way and make sense of the results. Introductory chapters explain how to use statistical methods and then the tests are arranged according to the type of data that they require. Diagrams are used to guide students toward the most appropriate tests. The focus is on nonparametric methods that make very few assumptions and are appropriate for the kinds of data that many students will collect. Parametric methods, including Student’s t-tests, correlation and regression are also covered. Although aimed directly at geography students at senior undergraduate and graduate level, this book provides an accessible introduction to a wide range of statistical methods and will be of value to students and researchers in allied disciplines including Earth and environmental science, and the social sciences.
| Author | : Clemens Reimann |
| Publisher | : John Wiley & Sons |
| Total Pages | : 380 |
| Release | : 2011-08-31 |
| Genre | : Science |
| ISBN | : 1119965284 |
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.
| Author | : Miguel F. Acevedo |
| Publisher | : CRC Press |
| Total Pages | : 561 |
| Release | : 2012-12-07 |
| Genre | : Mathematics |
| ISBN | : 143988501X |
Providing a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to implement data analysis methods using open-source software. Given the importance of interdisciplinary work in sustainability, the book brings together principles of statistics and probability, multivariate analysis, and spatial analysis methods applicable across a variety of science and engineering disciplines. Learn How to Use a Variety of Data Analysis and Statistics Methods Based on the author’s many years of teaching graduate and undergraduate students, this textbook emphasizes hands-on learning. Organized into two parts, it allows greater flexibility using the material in various countries and types of curricula. The first part covers probability, random variables and inferential statistics, applications of regression, time series analysis, and analysis of spatial point patterns. The second part uses matrix algebra to address multidimensional problems. After a review of matrices, it delves into multiple regression, dependent random processes and autoregressive time series, spatial analysis using geostatistics and spatial regression, discriminant analysis, and a variety of multivariate analyses based on eigenvector methods. Build from Fundamental Concepts to Effective Problem Solving Each chapter starts with conceptual and theoretical material to give a firm foundation in how the methods work. Examples and exercises illustrate the applications and demonstrate how to go from concepts to problem solving. Hands-on computer sessions allow students to grasp the practical implications and learn by doing. Throughout, the computer examples and exercises use seeg and RcmdrPlugin.seeg, open-source R packages developed by the author, which help students acquire the skills to implement and conduct analysis and to analyze the results. This self-contained book offers a unified presentation of data analysis methods for more effective problem solving. With clear, easy-to-follow explanations, the book helps students to develop a solid understanding of basic statistical analysis and prepares them for learning the more advanced and specialized methods they will need in their work.
| Author | : Maurizio Petrelli |
| Publisher | : Springer Nature |
| Total Pages | : 229 |
| Release | : 2021-09-16 |
| Genre | : Science |
| ISBN | : 3030780554 |
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.
