This course provides an introductory understanding of probability theory and a revision of basic statistical methods, with a modest exploration into the more sophisticated concepts of both. The topics covered in probability include counting and combinatorial methods, probability axioms, sample space, events, random variables, conditional expectation and the elementary properties of these constructs. Discrete and continuous random variables and the important univariate probability distributions will be covered in detail. Students will also be introduced to Bayes’ theorem and its applications. Limit theorems will be introduced. Students will see probability distributions in different settings via a wide range of problem-solving exercises.
The statistics component will be focused on computing and interpreting descriptive statistics and visual representation of quantitative data. Sampling and estimation will be introduced.