This is an intermediate level subject in the theory and practice of statistical inference. It extends STAT11-112 in the areas of probability and distribution theory, discrete and continuous random variables and joint distributional behaviour, as well as introducing principles of likelihood theory, estimation, confidence intervals and hypothesis tests. In addition, topics such as moment and cumulant generating functions are introduced, as well as an introduction to random sums and Central Limit Theorem based large-sample distributional approximations.
|Faculty||Bond Business School|
1. Explain the concepts of probability and calculate probabilities in a variety of scenarios.
2. Define and derive probability generating functions, moment generating functions and cumulant generating functions and use them to evaluate moments and cumulants and recognise distributions.
3. Define, apply and undertake calculations relating to basic discrete and continuous distributions.
4. Explain and apply the concepts of multivariate random variables, and their joint probability distributions.
5. Describe and apply the main methods of estimation and the main properties of estimators.
6. Construct and interpret a variety of confidence intervals and test a variety of hypotheses.
Assumed knowledge is the minimum level of knowledge of a subject area that students are assumed to have acquired through previous study. It is the responsibility of students to ensure they meet the assumed knowledge expectations of the subject. Students who do not possess this prior knowledge are strongly recommended against enrolling and do so at their own risk. No concessions will be made for students’ lack of prior knowledge.
Possess demonstrable knowledge in elementary probability theory, statistics, elementary calculus and linear algebra to the level of a unit such as STAT11-112 Quantitative Methods.
|Withdraw – Financial?||05/10/2019|
|Withdraw – Academic?||26/10/2019|
|Withdraw – Financial?||20/06/2020|
|Withdraw – Academic?||11/07/2020|