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Book
Handbook of meta-analysis in ecology and evolution
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ISBN: 9780691137292 9780691137285 0691137285 0691137293 Year: 2013 Publisher: Princeton : Princeton University Press,

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Abstract

Meta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This is the first comprehensive handbook of meta-analysis written specifically for ecologists and evolutionary biologists, and it provides an invaluable introduction for beginners as well as an up-to-date guide for experienced meta-analysts.The chapters, written by renowned experts, walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The handbook identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis (including when it should not be used). Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets. This one-of-a-kind resource is uniquely tailored to the biological sciences, and will provide an invaluable text for practitioners from graduate students and senior scientists to policymakers in conservation and environmental management. (-) Walks you through every step of carrying out a meta-analysis in ecology and evolutionary biology, from problem formulation to result presentation (-) Brings together experts from a broad range of fields (-) Shows how to avoid, minimize, or resolve pitfalls such as missing data, publication bias, varying data quality, nonindependence of observations, and phylogenetic dependencies among species (-) Helps you choose the right software (-) Draws on numerous examples based on real biological datasets


Book
Case Studies in Applied Bayesian Data Science : CIRM Jean-Morlet Chair, Fall 2018
Authors: --- ---
ISBN: 3030425533 3030425525 Year: 2020 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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Presenting a range of substantive applied problems within Bayesian Statistics along with their Bayesian solutions, this book arises from a research program at CIRM in France in the second semester of 2018, which supported Kerrie Mengersen as a visiting Jean-Morlet Chair and Pierre Pudlo as the local Research Professor. The field of Bayesian statistics has exploded over the past thirty years and is now an established field of research in mathematical statistics and computer science, a key component of data science, and an underpinning methodology in many domains of science, business and social science. Moreover, while remaining naturally entwined, the three arms of Bayesian statistics, namely modelling, computation and inference, have grown into independent research fields.While the research arms of Bayesian statistics continue to grow in many directions, they are harnessed when attention turns to solving substantive applied problems. Each such problem set has its own challenges and hence draws from the suite of research a bespoke solution. The book will be useful for both theoretical and applied statisticians, as well as practitioners, to inspect these solutions in the context of the problems, in order to draw further understanding, awareness and inspiration. .


Book
Mixtures : estimation and applications
Authors: --- ---
ISBN: 9781119993896 111999389X Year: 2011 Publisher: Hoboken: Wiley,

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Digital
Case Studies in Applied Bayesian Data Science : CIRM Jean-Morlet Chair, Fall 2018
Authors: --- ---
ISBN: 9783030425531 Year: 2020 Publisher: Cham Springer International Publishing

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Abstract

Presenting a range of substantive applied problems within Bayesian Statistics along with their Bayesian solutions, this book arises from a research program at CIRM in France in the second semester of 2018, which supported Kerrie Mengersen as a visiting Jean-Morlet Chair and Pierre Pudlo as the local Research Professor. The field of Bayesian statistics has exploded over the past thirty years and is now an established field of research in mathematical statistics and computer science, a key component of data science, and an underpinning methodology in many domains of science, business and social science. Moreover, while remaining naturally entwined, the three arms of Bayesian statistics, namely modelling, computation and inference, have grown into independent research fields.While the research arms of Bayesian statistics continue to grow in many directions, they are harnessed when attention turns to solving substantive applied problems. Each such problem set has its own challenges and hence draws from the suite of research a bespoke solution. The book will be useful for both theoretical and applied statisticians, as well as practitioners, to inspect these solutions in the context of the problems, in order to draw further understanding, awareness and inspiration. .


Book
Case Studies in Applied Bayesian Data Science
Authors: --- --- ---
ISBN: 9783030425531 Year: 2020 Publisher: Cham Springer International Publishing :Imprint: Springer

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Book
Statistical Methods for Hospital Monitoring with R
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ISBN: 1118596307 1118639154 1118639162 1118639170 Year: 2013 Publisher: John Wiley & Sons, Incorporated

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