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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| Main Author: | |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
[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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| 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. |
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| Physical Description: | 1 online resource |
| ISBN: | 9781959870029 |