EMBC+ MODULE 2: Toolbox for investigating marine Biodiversity

semester:

3

institute:

ects:

5

An introduction to R; Probability theory of relevance to population dynamics; Likelihood-based inference; Maximum likelihood estimation; Bayesian inference; WinBUGS; Density-independent population growth; Density-dependent population growth; Trophic interactions; Stochasticity; Environmental drivers; Population harvesting; State space analysis.

keywords:

Probability theory; Likelihood; Introduction to Bayesian inference; Model fitting; Optimization; Simulation; Population dynamics; Generalized linear models; Populations in time; Populations in space; R language; WinBUGS

teachers:

initial:

B.Sc. Honours introductory mathematics for science students; B.Sc. Honours introductory data analysis

final:

- An understanding of the underpinnings of statistical inference
- Proficiency in programming in R
- A working knowledge of population dynamics
- Ability to develop and apply advanced statistical models to population dynamics data
- Ability to draw inference on population dynamics
- Introductory understanding of Bayesian inference as applied to population dynamics.