| Description |
1 online resource (viii, 550) : illustrations |
| Contents |
About the Author -- Preface -- Models for Normally Distributed Responses -- What Variables to Include in a Model? -- Frequentist and Bayesian Inferential Frameworks -- Models for Non-Normal Data -- Models for Correlated Data -- Appendix -- References |
| Summary |
Ecological data pose many challenges to statistical inference. Most data come from observational studies rather than designed experiments; observational units are frequently sampled repeatedly over time, resulting in multiple, non-independent measurements; response data are often binary (e.g., presence-absence data) or non-negative integers (e.g., counts), and therefore, the data do not fit the standard assumptions of linear regression (Normality, independence, and constant variance). This book will familiarize readers with modern statistical methods that address these complexities using both frequentist and Bayesian frameworks |
| Bibliography |
Includes bibliographical references (pages 539-550) |
| Notes |
This work is licensed under a Creative Commons by Attribution 4.0 International License CC BY https://creativecommons.org/licenses/by/4.0 |
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Description based on online resource; title from title PDF, viewed July 30, 2024 |
| Subject |
Ecology -- Statistical methods -- Textbooks
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Ecology -- Mathematical models -- Textbooks
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Environmental sciences -- Statistical methods -- Textbooks
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Statistics -- Textbooks
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Bayesian statistical decision theory -- Textbooks
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| Form |
Electronic book
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| Author |
Open Textbook Library, distributor.
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University of Minnesota. Libraries. Publishing, publisher.
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| ISBN |
9781959870029 |
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1959870025 |
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