Statistics for Ecologists A Frequentist and Bayesian Treatment of Modern Regression Models
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., prese...
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| Format: | Electronic eBook |
| Language: | English |
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[Place of publication not identified]
University of Minnesota Libraries Publishing
2024.
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| Series: | Open textbook library.
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| Subjects: | |
| Online Access: | Access online version |
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| 100 | 1 | |a Fieberg, John R. |e author | |
| 245 | 0 | 0 | |a Statistics for Ecologists |b A Frequentist and Bayesian Treatment of Modern Regression Models |c John Fieberg |
| 264 | 2 | |a Minneapolis, MN |b Open Textbook Library | |
| 264 | 1 | |a [Place of publication not identified] |b University of Minnesota Libraries Publishing |c 2024. | |
| 264 | 4 | |c ©2024. | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 0 | |a Open textbook library. | |
| 505 | 0 | |a 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 | |
| 520 | 0 | |a 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. | |
| 542 | 1 | |f Attribution | |
| 546 | |a In English. | ||
| 588 | 0 | |a Description based on online resource | |
| 650 | 0 | |a Mathematics |v Textbooks | |
| 650 | 0 | |a Statistics |v Textbooks | |
| 650 | 0 | |a Science |v Textbooks | |
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| 856 | 4 | 0 | |u https://open.umn.edu/opentextbooks/textbooks/1588 |z Access online version |