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Book Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists

Download or read book Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists written by Howard B. Stauffer and published by John Wiley & Sons. This book was released on 2007-12-14 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first all-inclusive introduction to modern statistical research methods in the natural resource sciences The use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. However, many important contemporary methods of applied statistics, such as generalized linear modeling, mixed-effects modeling, and Bayesian statistical analysis and inference, remain relatively unknown among researchers and practitioners in this field. Through its inclusive, hands-on treatment of real-world examples, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists successfully introduces the key concepts of statistical analysis and inference with an accessible, easy-to-follow approach. The book provides case studies illustrating common problems that exist in the natural resource sciences and presents the statistical knowledge and tools needed for a modern treatment of these issues. Subsequent chapter coverage features: An introduction to the fundamental concepts of Bayesian statistical analysis, including its historical background, conjugate solutions, Bayesian hypothesis testing and decision-making, and Markov Chain Monte Carlo solutions The relevant advantages of using Bayesian statistical analysis, rather than the traditional frequentist approach, to address research problems Two alternative strategies—the a posteriori model selection strategy and the a priori parsimonious model selection strategy using AIC and DIC—to model selection and inference The ideas of generalized linear modeling (GLM), focusing on the most popular GLM of logistic regression An introduction to mixed-effects modeling in S-Plus® and R for analyzing natural resource data sets with varying error structures and dependencies Each statistical concept is accompanied by an illustration of its frequentist application in S-Plus® or R as well as its Bayesian application in WinBUGS. Brief introductions to these software packages are also provided to help the reader fully understand the concepts of the statistical methods that are presented throughout the book. Assuming only a minimal background in introductory statistics, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists is an ideal text for natural resource students studying statistical research methods at the upper-undergraduate or graduate level and also serves as a valuable problem-solving guide for natural resource scientists across a broad range of disciplines, including biology, wildlife management, forestry management, fisheries management, and the environmental sciences.

Book Introduction to Bayesian Methods in Ecology and Natural Resources

Download or read book Introduction to Bayesian Methods in Ecology and Natural Resources written by Edwin J. Green and published by Springer Nature. This book was released on 2020-11-26 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents modern Bayesian analysis in a format that is accessible to researchers in the fields of ecology, wildlife biology, and natural resource management. Bayesian analysis has undergone a remarkable transformation since the early 1990s. Widespread adoption of Markov chain Monte Carlo techniques has made the Bayesian paradigm the viable alternative to classical statistical procedures for scientific inference. The Bayesian approach has a number of desirable qualities, three chief ones being: i) the mathematical procedure is always the same, allowing the analyst to concentrate on the scientific aspects of the problem; ii) historical information is readily used, when appropriate; and iii) hierarchical models are readily accommodated. This monograph contains numerous worked examples and the requisite computer programs. The latter are easily modified to meet new situations. A primer on probability distributions is also included because these form the basis of Bayesian inference. Researchers and graduate students in Ecology and Natural Resource Management will find this book a valuable reference.

Book A Handbook of Basic Statistical Analyses using SPSS

Download or read book A Handbook of Basic Statistical Analyses using SPSS written by Mohammad Nasir bin Abdullah and published by Bootstrap Resources. This book was released on 2017-07-01 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This well respected text is designed for the first course in statistics and SPSS taken by students majoring in Business, Health, and Medicine. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with no statistical background. The examples in this book were chosen specifically for students in business, health, and medicine which include opportunities for real data analysis

Book Bayesian Models

    Book Details:
  • Author : N. Thompson Hobbs
  • Publisher : Princeton University Press
  • Release : 2015-08-04
  • ISBN : 0691159289
  • Pages : 314 pages

Download or read book Bayesian Models written by N. Thompson Hobbs and published by Princeton University Press. This book was released on 2015-08-04 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals. This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management. Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticians Covers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and more Deemphasizes computer coding in favor of basic principles Explains how to write out properly factored statistical expressions representing Bayesian models

Book Janus Faced Probability

Download or read book Janus Faced Probability written by Paolo Rocchi and published by Springer. This book was released on 2014-04-25 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of probability interpretation was long overlooked before exploding in the 20th century, when the frequentist and subjectivist schools formalized two conflicting conceptions of probability. Beyond the radical followers of the two schools, a circle of pluralist thinkers tends to reconcile the opposing concepts. The author uses two theorems in order to prove that the various interpretations of probability do come into opposition and can be used in different contexts. The goal here is to clarify the multi fold nature of probability by means of a purely mathematical approach and to show how philosophical arguments can only serve to deepen actual intellectual contrasts. The book can be considered as one of the most important contributions in the analysis of probability interpretation in the last 10-15 years.

Book Agent Based and Individual Based Modeling

Download or read book Agent Based and Individual Based Modeling written by Steven F. Railsback and published by Princeton University Press. This book was released on 2019-03-26 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential textbook on agent-based modeling—now fully updated and expanded Agent-Based and Individual-Based Modeling has become the standard textbook on the subject for classroom use and self-instruction. Drawing on the latest version of NetLogo and fully updated with new examples, exercises, and an enhanced text for easier comprehension, this is the essential resource for anyone seeking to understand how the dynamics of biological, social, and other complex systems arise from the characteristics of the agents that make up these systems. Steven Railsback and Volker Grimm lead students stepwise through the processes of designing, programming, documenting, and doing scientific research with agent-based models, focusing on the adaptive behaviors that make these models necessary. They cover the fundamentals of modeling and model analysis, introduce key modeling concepts, and demonstrate how to implement them using NetLogo. They also address pattern-oriented modeling, an invaluable strategy for modeling real-world problems and developing theory. This accessible and authoritative book focuses on modeling as a tool for understanding real complex systems. It explains how to pose a specific question, use observations from actual systems to design models, write and test software, and more. A hands-on introduction that guides students from conceptual design to computer implementation to analysis Filled with new examples and exercises and compatible with the latest version of NetLogo Ideal for students and researchers across the natural and social sciences Written by two leading practitioners Supported by extensive instructional materials at www.railsback-grimm-abm-book.com

Book Modeling Populations of Adaptive Individuals

Download or read book Modeling Populations of Adaptive Individuals written by Steven F. Railsback and published by Princeton University Press. This book was released on 2020-05-19 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book offers a new theory for modeling how organisms make tradeoff decisions and how these decisions affect both individuals and populations. Tradeoff decisions (or behaviors) are those that are optimize survival and include behaviors like foraging and reproduction. Existing theories have not painted a complete picture of tradeoff decisions because they only observe how the decisions of an individual affect them rather than how individuals impact, and are impacted by, the behavior of their communities. The authors' theory-which they call state and prediction based theory-uses individual-based models since these models show the complex ways that organisms relate to their environment. The authors' broader approach, one that integrates behavior and population dynamics, allows ecologists to see how individuals make adaptive tradeoff decisions. In simpler terms, this theory does not assume, as the previous models do, that future conditions are fixed, known, and unaffected by the behavior of others. Instead, the authors assume individuals make decisions like people do, which is by forecasting future conditions, using approximation to make good decisions, and updating their choices as conditions change"--

Book Good Statistical Practice for Natural Resources Research

Download or read book Good Statistical Practice for Natural Resources Research written by Roger Stern and published by CABI. This book was released on 2004 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part 1: Introduction Chapter 1: What is Natural Resources Research? Chapter 2: At Least Read This. Chapter 3: Sidetracks Part 2: Planning Chapter 4: Introduction to Research Planning Chapter 5: Concepts Underlying Experiments Chapter 6: Sampling Concepts Chapter 7: Surveys and Studies of Human Subjects Chapter 8: Surveying Land and Natural Populations Chapter 9: Planning Effective Experiments Part 3: Data Management Chapter 10: Data Management Issues and Problems Chapter 11: Use of Spreadsheet Packages Chapter 12: The Role of a Database Package Chapter 13: Developing a Data Management Strategy Chapter 14: Use of Statistical Software Part 4: Analysis Chapter 15: Analysis - Aims and Approaches Chapter 16: The DIY Toolbox - General Ideas 16.1 Opening the Toolbox 221 Chapter 17: Analysis of Survey Data Chapter 18: Analysis of Experimental Data Chapter 19: General Linear Models Chapter 20: The Craftsman's Toolbox Chapter 21: Informative Presentation of Tables, Graphs and Statistics Part 5: Where Next? Chapter 22: Current Trends and their Implications for Good Practice Chapter 23: Resources and Further Reading.

Book Mathematical Reviews

Download or read book Mathematical Reviews written by and published by . This book was released on 2008 with total page 984 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Likelihood Methods in Biology and Ecology

Download or read book Likelihood Methods in Biology and Ecology written by Michael Brimacombe and published by CRC Press. This book was released on 2018-12-18 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book emphasizes the importance of the likelihood function in statistical theory and applications and discusses it in the context of biology and ecology. Bayesian and frequentist methods both use the likelihood function and provide differing but related insights. This is examined here both through review of basic methodology and also the integr

Book Statistics for Earth and Environmental Scientists

Download or read book Statistics for Earth and Environmental Scientists written by John H. Schuenemeyer and published by John Wiley & Sons. This book was released on 2011-04-12 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book AMSTAT News

    Book Details:
  • Author : American Statistical Association
  • Publisher :
  • Release : 2008
  • ISBN :
  • Pages : 504 pages

Download or read book AMSTAT News written by American Statistical Association and published by . This book was released on 2008 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Bayesian Statistical Methods

Download or read book Bayesian Statistical Methods written by Brian J. Reich and published by CRC Press. This book was released on 2019-04-12 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. This book focuses on Bayesian methods applied routinely in practice including multiple linear regression, mixed effects models and generalized linear models (GLM). The authors include many examples with complete R code and comparisons with analogous frequentist procedures. In addition to the basic concepts of Bayesian inferential methods, the book covers many general topics: Advice on selecting prior distributions Computational methods including Markov chain Monte Carlo (MCMC) Model-comparison and goodness-of-fit measures, including sensitivity to priors Frequentist properties of Bayesian methods Case studies covering advanced topics illustrate the flexibility of the Bayesian approach: Semiparametric regression Handling of missing data using predictive distributions Priors for high-dimensional regression models Computational techniques for large datasets Spatial data analysis The advanced topics are presented with sufficient conceptual depth that the reader will be able to carry out such analysis and argue the relative merits of Bayesian and classical methods. A repository of R code, motivating data sets, and complete data analyses are available on the book’s website. Brian J. Reich, Associate Professor of Statistics at North Carolina State University, is currently the editor-in-chief of the Journal of Agricultural, Biological, and Environmental Statistics and was awarded the LeRoy & Elva Martin Teaching Award. Sujit K. Ghosh, Professor of Statistics at North Carolina State University, has over 22 years of research and teaching experience in conducting Bayesian analyses, received the Cavell Brownie mentoring award, and served as the Deputy Director at the Statistical and Applied Mathematical Sciences Institute.

Book Journal of the American Statistical Association

Download or read book Journal of the American Statistical Association written by and published by . This book was released on 2009 with total page 898 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Choice

Download or read book Choice written by and published by . This book was released on 2008 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Statistics in Natural Resources

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 333 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.

Book Statistical Methods in Water Resources

Download or read book Statistical Methods in Water Resources written by D.R. Helsel and published by Elsevier. This book was released on 1993-03-03 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.