Eco Stats Data Analysis In Ecology


Eco Stats Data Analysis In Ecology
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Eco Stats Data Analysis In Ecology


Eco Stats Data Analysis In Ecology
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Author : David I Warton
language : en
Publisher: Springer Nature
Release Date : 2022-08-10

Eco Stats Data Analysis In Ecology written by David I Warton and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-10 with Mathematics categories.


This book introduces ecologists to the wonderful world of modern tools for data analysis, especially multivariate analysis. For biologists with relatively little prior knowledge of statistics, it introduces a modern, advanced approach to data analysis in an intuitive and accessible way. The book begins by reviewing some core principles in statistics, and relates common methods to the linear model, a general framework for modeling data where the response is continuous. This is then extended to discrete data using generalized linear models, to designs with multiple sampling levels via mixed models, and to situations where there are multiple response variables via model-based approaches to multivariate analysis. Along the way there is an introduction to: important principles in model selection; adaptations of the model to handle non-linearity and cyclical variables; dependence due to structured correlation in time, space or phylogeny; and design-based techniques for inference that can relax some of the modelling assumptions. It concludes with a range of advanced topics in model-based multivariate analysis relevant to the modern ecologist, including fourth corner, latent variable and copula models. Examples span a variety of applications including environmental monitoring, species distribution modeling, global-scale surveys of plant traits, and small field experiments on biological controls. Math Boxes throughout the book explain some of the core ideas mathematically for readers who want to delve deeper, and R code is used throughout. Accompanying code, data, and solutions to exercises can be found in the ecostats R package on CRAN.



Analyzing Ecological Data


Analyzing Ecological Data
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Author : Alain Zuur
language : en
Publisher: Springer
Release Date : 2007-08-29

Analyzing Ecological Data written by Alain Zuur and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-29 with Science categories.


This book provides a practical introduction to analyzing ecological data using real data sets. The first part gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modeling techniques), multivariate analysis, time series analysis, and spatial statistics. The second part provides 17 case studies. The case studies include topics ranging from terrestrial ecology to marine biology and can be used as a template for a reader’s own data analysis. Data from all case studies are available from www.highstat.com. Guidance on software is provided in the book.



Statistical Ecology In Practice


Statistical Ecology In Practice
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Author : Stephen Waite
language : en
Publisher: Addison-Wesley Longman Limited
Release Date : 2000-01

Statistical Ecology In Practice written by Stephen Waite and has been published by Addison-Wesley Longman Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01 with Science categories.


This text combines principles of good field ecology research design with practical statistical analysis, suited to the needs of advanced students taking Field Ecology courses or undertaking projects that contribute to their final degree classification.



Statistical Ecology


Statistical Ecology
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Author : John A. Ludwig
language : en
Publisher: John Wiley & Sons
Release Date : 1988-05-18

Statistical Ecology written by John A. Ludwig 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 1988-05-18 with Mathematics categories.


Ecological community data. Spatial pattern analysis. Species-abundance relations. Species affinity. Community classification. Community ordination. Community interpretation.



Environmental And Ecological Statistics With R Second Edition


Environmental And Ecological Statistics With R Second Edition
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Author : Song S. Qian
language : en
Publisher: CRC Press
Release Date : 2016-11-03

Environmental And Ecological Statistics With R Second Edition written by Song S. Qian and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-03 with Mathematics categories.


Emphasizing the inductive nature of statistical thinking, Environmental and Ecological Statistics with R, Second Edition, connects applied statistics to the environmental and ecological fields. Using examples from published works in the ecological and environmental literature, the book explains the approach to solving a statistical problem, covering model specification, parameter estimation, and model evaluation. It includes many examples to illustrate the statistical methods and presents R code for their implementation. The emphasis is on model interpretation and assessment, and using several core examples throughout the book, the author illustrates the iterative nature of statistical inference. The book starts with a description of commonly used statistical assumptions and exploratory data analysis tools for the verification of these assumptions. It then focuses on the process of building suitable statistical models, including linear and nonlinear models, classification and regression trees, generalized linear models, and multilevel models. It also discusses the use of simulation for model checking, and provides tools for a critical assessment of the developed models. The second edition also includes a complete critique of a threshold model. Environmental and Ecological Statistics with R, Second Edition focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding readers through the process of scientific problem solving and statistical model development, it eases the transition from scientific hypothesis to statistical model.



Statistics For Ecologists Using R And Excel


Statistics For Ecologists Using R And Excel
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Author : Mark Gardener
language : en
Publisher: Pelagic Publishing
Release Date : 2012-01-01

Statistics For Ecologists Using R And Excel written by Mark Gardener and has been published by Pelagic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-01 with Science categories.


This is a book about the scientific process and how we apply it to data in ecology. We will learn how to plan for data collection, how to assemble data, how to analyse data and finally how to present the results. The book uses Microsoft Excel and the powerful Open Source R program to carry out data handling as well as producing graphs. Who this book is for Students of ecology and environmental science will find this book aimed at them although many other scientists will find the text useful as the principles and data analysis are the same in many disciplines. No prior knowledge is assumed and the reader can develop their skills to degree level and beyond. What you will learn from this book How to plan ecological projects How to record and assemble your data How to use Excel for data analysis and graphs How to use R for data analysis and graphs How to carry out a wide range of statistical analyses How to create professional looking graphs How to present your results



Handbook Of Environmental And Ecological Statistics


Handbook Of Environmental And Ecological Statistics
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Author : Alan E. Gelfand
language : en
Publisher: CRC Press
Release Date : 2019-01-15

Handbook Of Environmental And Ecological Statistics written by Alan E. Gelfand and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-15 with Mathematics categories.


This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.



A Primer Of Ecological Statistics


A Primer Of Ecological Statistics
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Author : Nicholas J. Gotelli
language : en
Publisher: Sinauer
Release Date : 2013-03-14

A Primer Of Ecological Statistics written by Nicholas J. Gotelli and has been published by Sinauer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Science categories.


A Primer of Ecological Statistics, Second Edition explains fundamental material in probability theory, experimental design, and parameter estimation for ecologists and environmental scientists. The book emphasizes a general introduction to probability theory and provides a detailed discussion of specific designs and analyses that are typically encountered in ecology and environmental science. Appropriate for use as either a stand-alone or supplementary text for upper-division undergraduate or graduate courses in ecological and environmental statistics, ecology, environmental science, environmental studies, or experimental design, the Primer also serves as a resource for environmental professionals who need to use and interpret statistics daily but have little or no formal training in the subject. The book is divided into four parts. Part I discusses the fundamentals of probability and statistical thinking. It introduces the logic and language of probability (Chapter 1), explains common statistical distributions used in ecology (Chapter 2) and important measures of central tendency and spread (Chapter 3), explains P-values, hypothesis testing, and statistical errors (Chapter 4), and introduces frequentist, Bayesian, and Monte Carlo methods of analysis (Chapter 5). Part II discusses how to successfully design and execute field experiments and sampling studies. Topics include design strategies (Chapter 6), a 'bestiary' of experimental designs (Chapter 7), and transformations and data management (Chapter 8). Part III discusses specific analyses, and covers the material that is the main core of most statistics texts. Topics include regression (Chapter 9), analysis of variance (Chapter 10), categorical data analysis (Chapter 11), and multivariate analysis (Chapter 12). Part IV—new to this edition—discusses two central topics in estimating important ecological metrics. Topics include quantification of biological diversity (Chapter 13) and estimating occupancy, detection probability, and population sizes from marked and unmarked populations (Chapter 14). The book includes a comprehensive glossary, a mathematical appendix on matrix algebra, and extensively annotated tables and figures. Footnotes introduce advanced and ancillary material: some are purely historical, others cover mathematical/statistical proofs or details, and still others address current topics in the ecological literature. Data files and code used for some of the examples, as well as errata, are available online.



Data Analysis In Community And Landscape Ecology


Data Analysis In Community And Landscape Ecology
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Author : R. H. Jongman
language : en
Publisher: Cambridge University Press
Release Date : 1995-03-02

Data Analysis In Community And Landscape Ecology written by R. H. Jongman and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-03-02 with Mathematics categories.


Ecological data has several special properties: the presence or absence of species on a semi-quantitative abundance scale; non-linear relationships between species and environmental factors; and high inter-correlations among species and among environmental variables. The analysis of such data is important to the interpretation of relationships within plant and animal communities and with their environments. In this corrected version of Data Analysis in Community and Landscape Ecology, without using complex mathematics, the contributors demonstrate the methods that have proven most useful, with examples, exercises and case-studies. Chapters explain in an elementary way powerful data analysis techniques such as logic regression, canonical correspondence analysis, and kriging.



Models For Ecological Data


Models For Ecological Data
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Author : James S. Clark
language : en
Publisher: Princeton University Press
Release Date : 2020-10-06

Models For Ecological Data written by James S. Clark and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-06 with Science categories.


The environmental sciences are undergoing a revolution in the use of models and data. Facing ecological data sets of unprecedented size and complexity, environmental scientists are struggling to understand and exploit powerful new statistical tools for making sense of ecological processes. In Models for Ecological Data, James Clark introduces ecologists to these modern methods in modeling and computation. Assuming only basic courses in calculus and statistics, the text introduces readers to basic maximum likelihood and then works up to more advanced topics in Bayesian modeling and computation. Clark covers both classical statistical approaches and powerful new computational tools and describes how complexity can motivate a shift from classical to Bayesian methods. Through an available lab manual, the book introduces readers to the practical work of data modeling and computation in the language R. Based on a successful course at Duke University and National Science Foundation-funded institutes on hierarchical modeling, Models for Ecological Data will enable ecologists and other environmental scientists to develop useful models that make sense of ecological data. Consistent treatment from classical to modern Bayes Underlying distribution theory to algorithm development Many examples and applications Does not assume statistical background Extensive supporting appendixes Lab manual in R is available separately