| Delivery Type | Delivery length / details |
|---|---|
| Lecture | 19 Hours. (19 x 1 hour lectures) |
| Seminars / Tutorials | 3 Hours. (3 x 1 hour example classes) |
| Assessment Type | Assessment length / details | Proportion |
|---|---|---|
| Semester Exam | 2 Hours (written examination) | 100% |
| Supplementary Assessment | 2 Hours (written examination) | 100% |
On completion of this module, a student should be able to:
1. describe the relationships between the joint, marginal, conditional probability (density) functions, cumulative distribution function of bivariate random variables and move between these;
2. test for independence of two random variables;
3. calculate distributions of functions of random variables in univariate and simple bibivariate cases;
4. use moment generating functions to determine moments and distributions of sums of random variables;
5. describe how the chi-squared, t and F distributions arise from a Normal random sample, and use the associated tables;
6. calculate maximum likelihood estimators;
7. apply the criterion of unbiasedness.
In many situations in statistics and probability it is necessary to handle more than one random variable at the same time. This module covers techniques needed to do this, and also to deal with functions of random variables. Particular attention will be paid to the case of random variables arising from a Normal random sample. The module concludes with some material on the theory of estimation.
This module will provide a thorough grounding in distribution theory for several random variables, and will also consolidate the material on estimation introduced in MA11310.
This module is at CQFW Level 6