Statistical Methods for Field and Laboratory Studies in Behavioral Ecology

✍ Scribed by Pardo, Michael; Pardo, Scott

• Publisher: CRC Press
• Year: 2018
• Tongue: English
• Leaves: 319
• Series: Chapman & Hall/CRC Applied Environmental Statistics
• Edition: First edition
• Category: Library

✦ Synopsis

""--Provided by publisher.

Abstract: ""--Provided by publisher

✦ Table of Contents

Content: Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface
Acknowledgments
About the Authors
Chapter 1: Statistical Foundations
Some Probability Concepts
Some Statistical Concepts
Key Points for Chapter 1
Chapter 2: Binary Results: Single Samples and 2 Ã#x97
2 Tables
General Ideas
Single Proportion
2 Ã#x97
2 Tables
Examples with R Code
Single Proportion
2 Ã#x97
2 Tables
Theoretical Aspects
Single Proportion
2 Ã#x97
2 Tables
Key Points for Chapter 2
Chapter 3: Continuous Variables
General Ideas
Examples with R Code
Theoretical Aspects
Key Points for Chapter 3. Chapter 4: The Linear Model: Continuous VariablesGeneral Ideas
Examples with R Code
Theoretical Aspects
Key Points for Chapter 4
Chapter 5: The Linear Model: Discrete Regressor Variables
General Ideas
Examples with R Code
More Than One Treatment: Multiple Factors
Blocking Factors
ANOVA and Permutation Tests
Nested Factors
Analysis of Covariance: Models with Both Discrete and Continuous Regressors
Theoretical Aspects
Multiple Groupings: One-Way ANOVA
Key Points for Chapter 5
Chapter 6: The Linear Model: Random Effects and Mixed Models
General Ideas. Simple Case: One Fixed and One Random EffectExamples with R Code
More Complex Case: Multiple Fixed and Random Effects
Theoretical Aspects
Key Points for Chapter 6
Chapter 7: Polytomous Discrete Variables: R Ã#x97
C Contingency Tables
General Ideas
Independence of Two Discrete Variables
Examples with R Code
A Goodness-of-Fit Test
A Special Goodness-of-Fit Test: Test for Random Allocation
Theoretical Aspects
Key Points for Chapter 7
Chapter 8: The Generalized Linear Model: Logistic and Poisson Regression
General Ideas
Binary Logistic Regression
Examples with R Code. The Logit TransformationPoisson Regression
Overdispersion
Zero-Inflated Data and Poisson Regression
Theoretical Aspects
Logistic Regression
Poisson Regression
Overdispersed Poisson
Zero-Inflated Poisson
Key Points for Chapter 8
Chapter 9: Multivariate Analyses: Dimension Reduction, Clustering, and Discrimination
General Ideas
Dimension Reduction: Principal Components
Clustering
Discrimination
MANOVA
Examples with R Code
Dimension Reduction: Principal Components
Clustering
Discrimination
MANOVA
Theoretical Aspects
Principal Components
Discrimination
MANOVA. Key Points for Chapter 9Chapter 10: Bayesian and Frequentist Philosophies
General Ideas
Bayesâ#x80
#x99
Theorem: Not Controversial
Conjugacy
Beta, Binomial
Poisson, Gamma
Normal, Normal
Monte Carlo Markov Chain (MCMC) Method
Examples with R Code
Exponential, Gamma
Bayesian Regression Analysis
Markov Chain Monte Carlo
Theoretical Aspects
Bayesian Regression Analysis
A Slightly More Complicated Model
An Afterword about Bayesian Methods
Key Points for Chapter 10
Chapter 11: Decision and Game Theory
General Ideas
Examples with R Code
Discrete Choices, Discrete States.

✦ Subjects

Animal ecology -- Mathematical models.;Animal populations -- Mathematical models.;Mathematical statistics.;SCIENCE / Life Sciences / Ecology.;Human ecology.