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
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.