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

Dublin Core

Title

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

Subject

Statistics

Description

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.

Creator

John R. Fieberg

Source

https://conservancy.umn.edu/handle/11299/260227

Publisher

University of Minnesota Libraries Publishing

Date

2024

Contributor

Baihaqi

Rights

Creative Commons

Format

PDF

Language

English

Type

Textbooks

Files

Statistics4Ecologists.pdf.jpg

Collection

Citation

John R. Fieberg, “Statistics for Ecologists: A Frequentist and Bayesian Treatment of Modern Regression Models,” Open Educational Resource (OER) - USK Library, accessed April 24, 2025, http://202.4.186.74:8004/oer/items/show/7759.

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