Statistical Analysis in Population Ecology

EMBC+ MODULE 2: Toolbox for investigating marine Biodiversity
semester: 
3
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
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.