Introduction to Bayesian inference
1
Introduction: Modes of inference
Bayesian Inference for Biologists
Welcome
Introduction to Bayesian inference
1
Introduction: Modes of inference
2
Probability and Bayes’ theorem
3
Introduction to JAGS and MCMC
Example analyses with JAGS and R
4
Linear models, Bayesian style
5
GLM for count data
6
GLM for binomial data
7
GLM for continuous data
8
Nonlinear models in JAGS
9
Mixed models and random effects
Special applications of Bayesian inference
10
10-mark-recapture.html
11
State space models
References
Table of contents
1.1
Motivation: hypothesis testing in biology
1.2
Null hypothesis significance testing and
p
-values
1.3
Maximum likelihood estimation (MLE)
1.4
Bayes’ Theorem
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Introduction to Bayesian inference
1
Introduction: Modes of inference
1
Introduction: Modes of inference
1.1
Motivation: hypothesis testing in biology
1.2
Null hypothesis significance testing and
p
-values
1.3
Maximum likelihood estimation (MLE)
1.4
Bayes’ Theorem
Introduction to Bayesian inference
2
Probability and Bayes’ theorem