Modelling Environmental Systems (ENVSCI 310)
Quantitative models have become a key component of the ecologist’s toolkit. This course provides an introduction to how models are used in the study and management of environmental impacts in a range of natural environments (e.g. terrestrial, fluvial, atmospheric, subterranean, coastal). You will develop skills in designing and critically assessing different types (numerical, empirical and simulation) of models of the environment.
A key component of this course are computer-based laboratory sessions in which you are exposed to a range of different approaches and methodologies for environmental modelling; these sessions cover a range of topics including individual species population dynamics, air pollution in urban environments and spatial models of social systems.
Applied Multivariate Analysis (STATS 302)
This course covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics studied include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate regression and associated methods. The approach will be largely non-mathematical and practical, with an emphasis on the understanding of the techniques.
The laboratories cover techniques for data display, dimension reduction and ordination, cluster analysis, multivariate regression and associated methods. The approach is largely non-mathematical and practical, with an emphasis on the understanding of the techniques.
Advanced Statistical Modelling (STATS 330)
This course considers the application of the generalised linear model to fit data arising from a wide range of sources, including multiple linear regression models, log-linear models and logistic regression models. This information is essential knowledge for the statistical analysis of ecological data.
The laboratories consider techniques for the graphical exploration of data and the application of the generalized linear model to fit data arising from sources such as multiple linear regression models, log-linear models and logistic regression models.
Design and Analysis of Surveys (STATS 341)
This course looks at the design and analysis of the sample survey, including surveys in a biological context.
The laboratories consider survey design, data management and information systems, and the analysis of data from simple random, stratified, cluster and multistage sampling.