*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

An introduction to probability theory and statistical methods especially as they relate to public policy. The course will consist of a brief introduction to probability theory as well as various ...

This course introduces students to statistics and quantitative information. The course surveys probability theory, hypothesis testing, descriptive statistics and visualizations, and inferential ...

Probability theory constitutes the mathematical framework for quantifying uncertainty and analysing random phenomena. Its foundations lie in measure theory, where a probability space is defined as a ...

Introduction to probability theory and its applications. Axioms of probability, distributions, discrete and continuous random variables, conditional and joint distributions, correlation, limit laws, ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

Collecting data; summarizing and displaying data; drawing conclusions and making decisions using data; probability background, confidence intervals, hypotheses tests, regression, correlation. Not open ...

Circular statistics is a specialised subfield of statistics that focuses on analysing data points distributed on a circle. Unlike conventional linear statistics, circular data is characterised by ...

This course is available on the MSc in Quantitative Methods for Risk Management. This course is available with permission as an outside option to students on other programmes where regulations permit.

Economics is the study of the allocation of scarce resources. The subject of this course is microeconomics, which examines the decision making of individuals and firms with regard to consumption, ...