Advanced statistics: distribution theory (half course)
С открытой датой
Описание мероприятияЯзык обучения: английский
This half-course is intended for students who already have some grounding in statistics. It provides the basis for an advanced course in statistical inference.
Aims and objectives
The aim of this course is to provide a thorough theoretical grounding in probability distributions. The course teaches fundamental material that is required for specialised courses in statistics, actuarial science and econometrics.
This half course is assessed by a two-hour unseen written examination.
- Probability: Probability measure. Conditional probability. Bayes’ theorem.
- Distribution Theory: Distribution function. Mass and density. Expectation operator. Moments, moment generating functions, cumulant generating functions. Convergence concepts.
- Multivariate Distributions: Joint distributions. Conditional distributions, conditional moments.
- Functions of random variables.
At the end of this half course and having completed the essential reading and activities students should be able to:
- recall a large number of distributions and be a competent user of their mass/density and distribution functions and moment generating functions
- explain relationships between variables, conditioning, independence and correlation
- relate the theory and method taught in the unit to solve practical problems.
Требования к поступающим:
If taken as part of a BSc degree, courses which must be passed before this half course may be attempted:
- ST104a Statistics 1 and
- ST104b Statistics 2.