The course consists of two parts. One covers introductory probability theory. This
- events and sample spaces, simple and joint probability, conditional probability,Bayes' theorem,
- discrete probability distributions, including binomial distribution, Poisson distribution, hypergeometrical distribution,
- continuous distributions, including normal and uniform distributions, and
- sampling distributions of the mean and proportion, the central limit theorem.
The other covers descriptive statistics. This includes
- data collection, measurement scales, sampling methods, and
- graphical and numerical methods for summarising and presenting data.