Download or read book Statistical Methods and Applications in Forestry and Environmental Sciences written by Girish Chandra and published by Springer Nature. This book was released on 2020-01-04 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent developments in statistical methodologies with particular relevance to applications in forestry and environmental sciences. It discusses important methodologies like ranked set sampling, adaptive cluster sampling, small area estimation, calibration approach-based estimators, design of experiments, multivariate techniques, Internet of Things, and ridge regression methods. It also covers the history of the implementation of statistical techniques in Indian forestry and the National Forest Inventory of India. The book is a valuable resource for applied statisticians, students, researchers, and practitioners in the forestry and environment sector. It includes real-world examples and case studies to help readers apply the techniques discussed. It also motivates academicians and researchers to use new technologies in the areas of forestry and environmental sciences with the help of software like R, MATLAB, Statistica, and Mathematica.

Download or read book From Experimental Network to Meta analysis written by David Makowski and published by Springer. This book was released on 2019-05-07 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has been designed as a methodological guide and shows the interests and limitations of different statistical methods to analyze data from experimental networks and to perform meta-analyses. It is intended for engineers, students and researchers involved in data analysis in agronomy and environmental science.

Download or read book Biometry for Forestry and Environmental Data written by Lauri Mehtatalo and published by CRC Press. This book was released on 2020-05-27 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biometry for Forestry and Environmental Data with Examples in R focuses on statistical methods that are widely applicable in forestry and environmental sciences, but it also includes material that is of wider interest. Features: · Describes the theory and applications of selected statistical methods and illustrates their use and basic concepts through examples with forestry and environmental data in R. · Rigorous but easily accessible presentation of the linear, nonlinear, generalized linear and multivariate models, and their mixed-effects counterparts. Chapters on tree size, tree taper, measurement errors, and forest experiments are also included. · Necessary statistical theory about random variables, estimation and prediction is included. The wide applicability of the linear prediction theory is emphasized. · The hands-on examples with implementations using R make it easier for non-statisticians to understand the concepts and apply the methods with their own data. Lot of additional material is available at www.biombook.org. The book is aimed at students and researchers in forestry and environmental studies, but it will also be of interest to statisticians and researchers in other fields as well.

Download or read book Environmental Statistics written by Vic Barnett and published by John Wiley & Sons. This book was released on 2005-12-13 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: In modern society, we are ever more aware of the environmental issues we face, whether these relate to global warming, depletion of rivers and oceans, despoliation of forests, pollution of land, poor air quality, environmental health issues, etc. At the most fundamental level it is necessary to monitor what is happening in the environment – collecting data to describe the changing scene. More importantly, it is crucial to formally describe the environment with sound and validated models, and to analyse and interpret the data we obtain in order to take action. Environmental Statistics provides a broad overview of the statistical methodology used in the study of the environment, written in an accessible style by a leading authority on the subject. It serves as both a textbook for students of environmental statistics, as well as a comprehensive source of reference for anyone working in statistical investigation of environmental issues. Provides broad coverage of the methodology used in the statistical investigation of environmental issues. Covers a wide range of key topics, including sampling, methods for extreme data, outliers and robustness, relationship models and methods, time series, spatial analysis, and environmental standards. Includes many detailed practical and worked examples that illustrate the applications of statistical methods in environmental issues. Authored by a leading authority on environmental statistics.

Download or read book Hierarchical Modelling for the Environmental Sciences written by James Samuel Clark and published by Oxford University Press on Demand. This book was released on 2006 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: New statistical tools are changing the way in which scientists analyze and interpret data and models. Hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide a consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complicated, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences.

Download or read book Statistical Data Analysis Explained written by Clemens Reimann and published by John Wiley & Sons. This book was released on 2011-08-31 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Methods and Applications of Statistics in the Atmospheric and Earth Sciences written by Narayanaswamy Balakrishnan and published by John Wiley & Sons. This book was released on 2012-11-19 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the classic and cutting-edge quantitative methods for understanding environmental science research Based on the multifaceted 16-volume Encyclopedia of Statistical Sciences, Second Edition, Methods and Applications of Statistics in the Atmospheric and Earth Sciences offers guidance on the application of statistical methods for conducting research in these fields of study. With contributions from more than 100 leading experts in academia and industry, this volume combines key articles from the Encyclopedia with newly developed topics addressing some of the more critical issues, including pollution, droughts, and volcanic activity. Readers will gain a thorough understanding of cutting-edge methods for the acquisition and analysis of data across a wide range of subject areas, from geophysics, geology, and biogeography to meteorology, forestry, agriculture, animal science, and ornithology. The book features new and updated content on quantitative methods and their use in understanding the latest topics in social research, including: Drought Analysis and Forecasting Childhood Obesity Ranked Set Sampling Methodology for Environmental Data Species Richness and Shared Species Richness Geographic Information Systems Each contribution offers authoritative yet easily accessible coverage of statistical concepts. With updated references and discussion of emerging topics, readers are provided with the various statistical methods, techniques, strategies, and applications that are essential for tackling critical issues in environmental science research. Featuring a balance of classical and cutting-edge methodologies, Methods and Applications of Statistics in the Atmospheric and Earth Sciences is an excellent resource for researchers, professionals, and students in the fields of sociology, psychology, philosophy, education, political science, and the related disciplines who would like to learn about the uses of statistics in gathering, reporting, and analyzing data.

Download or read book Practical Environmental Statistics and Data Analysis written by Yue Rong and published by ILM Publications. This book was released on 2011 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Describes the application of statistical methods in different environmental fields, with an emphasis on how to solve real-world problems in complex systems"--Provided by publisher.

Download or read book Statistical Methods for Trend Detection and Analysis in the Environmental Sciences written by Richard Chandler and published by John Wiley & Sons. This book was released on 2011-03-25 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monitoring the effect of intervening in some environmental system. This book provides an overview of modern statistical techniques that may be relevant in problems of this nature. Practitioners studying environmental change will be familiar with many classical statistical procedures for the detection and estimation of trends. However, the ever increasing capacity to collect and process vast amounts of environmental information has led to growing awareness that such procedures are limited in the insights that they can deliver. At the same time, significant developments in statistical methodology have often been widely dispersed in the statistical literature and have therefore received limited exposure in the environmental science community. This book aims to provide a thorough but accessible review of these developments. It is split into two parts: the first provides an introduction to this area and the second part presents a collection of case studies illustrating the practical application of modern statistical approaches to the analysis of trends in real studies. Key Features: Presents a thorough introduction to the practical application and methodology of trend analysis in environmental science. Explores non-parametric estimation and testing as well as parametric techniques. Methods are illustrated using case studies from a variety of environmental application areas. Looks at trends in all aspects of a process including mean, percentiles and extremes. Supported by an accompanying website featuring datasets and R code. The book is designed to be accessible to readers with some basic statistical training, but also contains sufficient detail to serve as a reference for practising statisticians. It will therefore be of use to postgraduate students and researchers both in the environmental sciences and in statistics.

Download or read book Contemporary Statistical Models for the Plant and Soil Sciences written by Oliver Schabenberger and published by CRC Press. This book was released on 2001-11-13 with total page 762 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite its many origins in agronomic problems, statistics today is often unrecognizable in this context. Numerous recent methodological approaches and advances originated in other subject-matter areas and agronomists frequently find it difficult to see their immediate relation to questions that their disciplines raise. On the other hand, statisticians often fail to recognize the riches of challenging data analytical problems contemporary plant and soil science provides. The first book to integrate modern statistics with crop, plant and soil science, Contemporary Statistical Models for the Plant and Soil Sciences bridges this gap. The breadth and depth of topics covered is unusual. Each of the main chapters could be a textbook in its own right on a particular class of data structures or models. The cogent presentation in one text allows research workers to apply modern statistical methods that otherwise are scattered across several specialized texts. The combination of theory and application orientation conveys ìwhyî a particular method works and ìhowî it is put in to practice. About the downloadable resources The accompanying downloadable resources are a key component of the book. For each of the main chapters additional sections of text are available that cover mathematical derivations, special topics, and supplementary applications. It supplies the data sets and SAS code for all applications and examples in the text, macros that the author developed, and SAS tutorials ranging from basic data manipulation to advanced programming techniques and publication quality graphics. Contemporary statistical models can not be appreciated to their full potential without a good understanding of theory. They also can not be applied to their full potential without the aid of statistical software. Contemporary Statistical Models for the Plant and Soil Science provides the essential mix of theory and applications of statistical methods pertinent to research in life sciences.

Download or read book Statistics in Natural Resources written by Matthew Russell and published by CRC Press. This book was released on 2022-08-19 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: To manage our environment sustainably, professionals must understand the quality and quantity of our natural resources. Statistical analysis provides information that supports management decisions and is universally used across scientific disciplines. Statistics in Natural Resources: Applications with R focuses on the application of statistical analyses in the environmental, agricultural, and natural resources disciplines. This is a book well suited for current or aspiring natural resource professionals who are required to analyze data and perform statistical analyses in their daily work. More seasoned professionals who have previously had a course or two in statistics will also find the content familiar. This text can also serve as a bridge between professionals who understand statistics and want to learn how to perform analyses on natural resources data in R. The primary goal of this book is to learn and apply common statistical methods used in natural resources by using the R programming language. If you dedicate considerable time to this book, you will: Develop analytical and visualization skills for investigating the behavior of agricultural and natural resources data. Become competent in importing, analyzing, and visualizing complex data sets in the R environment. Recode, combine, and restructure data sets for statistical analysis and visualization. Appreciate probability concepts as they apply to environmental problems. Understand common distributions used in statistical applications and inference. Summarize data effectively and efficiently for reporting purposes. Learn the tasks required to perform a variety of statistical hypothesis tests and interpret their results. Understand which modeling frameworks are appropriate for your data and how to interpret predictions. Includes over 130 exercises in R, with solutions available on the book’s website.

Download or read book Statistical Methods for Environmental Sciences written by International Conference on Statistical Methods for Environmental Sciences and published by . This book was released on 1998 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Applied Statistical Methods written by David D. Hanagal and published by Springer Nature. This book was released on 2022-04-13 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects select contributions presented at the International Conference on Importance of Statistics in Global Emerging (ISGES 2020) held at the Department of Mathematics and Statistics, University of Pune, Maharashtra, India, from 2–4 January 2020. It discusses recent developments in several areas of statistics with applications of a wide range of key topics, including small area estimation techniques, Bayesian models for small areas, ranked set sampling, fuzzy supply chain, probabilistic supply chain models, dynamic Gaussian process models, grey relational analysis and multi-item inventory models, and more. The possible use of other models, including generalized Lindley shared frailty models, Benktander Gibrat risk model, decision-consistent randomization method for SMART designs and different reliability models are also discussed. This book includes detailed worked examples and case studies that illustrate the applications of recently developed statistical methods, making it a valuable resource for applied statisticians, students, research project leaders and practitioners from various marginal disciplines and interdisciplinary research.

Download or read book Geostatistics for Environmental Scientists written by Richard Webster and published by John Wiley & Sons. This book was released on 2007-10-22 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geostatistics is essential for environmental scientists. Weather and climate vary from place to place, soil varies at every scale at which it is examined, and even man-made attributes – such as the distribution of pollution – vary. The techniques used in geostatistics are ideally suited to the needs of environmental scientists, who use them to make the best of sparse data for prediction, and top plan future surveys when resources are limited. Geostatistical technology has advanced much in the last few years and many of these developments are being incorporated into the practitioner’s repertoire. This second edition describes these techniques for environmental scientists. Topics such as stochastic simulation, sampling, data screening, spatial covariances, the variogram and its modeling, and spatial prediction by kriging are described in rich detail. At each stage the underlying theory is fully explained, and the rationale behind the choices given, allowing the reader to appreciate the assumptions and constraints involved.

Download or read book Environmental Data Analysis written by Carsten Dormann and published by Springer Nature. This book was released on 2020-12-20 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Statistical Methods in Biology written by S.J. Welham and published by CRC Press. This book was released on 2014-08-22 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors’ experience. Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat® statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R. By the time you reach the end of the book (and online material) you will have gained: A clear appreciation of the importance of a statistical approach to the design of your experiments, A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables, Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly, An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working. The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.

Download or read book Spatial Modeling in GIS and R for Earth and Environmental Sciences written by Hamid Reza Pourghasemi and published by Elsevier. This book was released on 2019-01-18 with total page 798 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear link between GIS and open source software is essential for the study of spatial objects or phenomena that occur in the real world and facilitate problem-solving. Organized into clear sections on applications and using case studies, the book helps researchers to more quickly understand GIS data and formulate more complex conclusions. The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and environmental science, especially those looking to better utilize GIS and spatial modeling. Offers a clear, interdisciplinary guide to serve researchers in a variety of fields, including hazards, land surveying, remote sensing, cartography, geophysics, geology, natural resources, environment and geography Provides an overview, methods and case studies for each application Expresses concepts and methods at an appropriate level for both students and new users to learn by example