The objective of this course is to introduce students to the fundamentals of probability and inferential statistics, within the context of biological problems. The course consists of three main sections: summarizing data using graphical and tabular methods, defining and manipulating probabilities, and testing biological hypotheses. The concepts will be illustrated by applying them to problems from the biological sciences. The laboratories introduce students to the use of EXCEL™ to solve statistical problems and summarize data graphically.
The objective of this course is to expose students to the use of mathematical models to represent hypotheses about population dynamics processes and to evaluate the implications of alternative management policies. Four major themes are considered: how to develop mathematical models based on population dynamic hypotheses; typical models used in fisheries stock assessment; fitting models to data; and evaluating the consequences of alternative management policies. Laboratories involve using Excel™ and Visual Basic for Applications™ to implement a range of models.
This seven-lecture course introduces students to the basics of programming in R. The lecture series will cover how to construct functions in R and how to use R to fit models to data and summarise the results of model fits graphically as well as using confidence intervals. Model selection will also be discussed briefly. Students completing this course will have much of the background needed to take the SAFS upper level stock assessment courses (FISH 458, 557, 558, 559).
Many of the questions confronted by biologists relate to conducting decision analyses, e.g. what are the consequences of implementing a Marine Reserve or reductions in catch limits in terms of the impact on yield and conservation of species. This course introduces students to how to use decision analysis to evaluate alternative management actions. The focus is on fisheries applications, but the models and techniques are applicable broadly in quantitative conservation biology. The course has two major themes: what is decision analysis and how does one conduct a decision analysis; and applying Bayesian methods to assign probabilities to alternative hypotheses and to conduct meta-analyses. Homework assignments use R to illustrate the topics covered during the lecture sequence.
The objective of this course is to expose students who have taken courses in the mathematical modeling and statistical model fitting to numerical methods, including the AD Model Builder package and WINBUGS. Modeling environments such as R are sufficient for conducting several types of analyses but more powerful techniques are often needed to solve research questions. The focus of this course will be on fisheries applications, but the models and techniques to be covered are broadly applicable in quantitative conservation biology.