Statistics for Ecologists: A Frequentist and Bayesian Treatment of Modern Regression Models

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Statistics for Ecologists: A Frequentist and Bayesian Treatment of Modern Regression Models

Published Date

2024-01

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University of Minnesota Libraries Publishing

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Book

Abstract

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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978-1-959870-02-9

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https://doi.org/10.24926/9781959870029

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Fieberg, John R. (2024). Statistics for Ecologists: A Frequentist and Bayesian Treatment of Modern Regression Models. Retrieved from the University Digital Conservancy, https://doi.org/10.24926/9781959870029.

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