- Module code: ST219
- Module name: Mathematical Statistics Part B
- Department: Statistics
- Credit: 12
Module content and teaching
To introduce the major ideas of statistical inference with an emphasis on likelihood methods of estimation and testing.
Principal learning outcomes
Understand the main notions of statistical inference including a (parametrized) statistical model, an estimator and its sampling distribution and hypothesis tests. Be able to calculate maximum likelihood estimators in a variety of examples. Be able to use likelihood rations to construct hypothesis tets in a variety of examples including the classical t and F tests. Be able to derive properties of sampling distributions of esimators in a variety of examples.
Timetabled teaching activities
30 hours of lectures, 5 hours of tutorials.
|Assessment group||Assessment name||Percentage|
|12 CATS (Module code: ST219-12)|
|D (Assessed/examined work)||Assessed Course Work||10%|
|Examination - Main Summer Exam Period (weeks 4-9)||90%|
This module is available on the following courses:
- Undergraduate Mathematics and Statistics (BSc MMathStat) (G1G3) - Year 2
- Undergraduate Master of Mathematics,Operational Research,Statistics and Economics (G300) - Year 2
- Undergraduate Data Science (G302) - Year 2
- Undergraduate Mathematics and Statistics (BSc) (GG14) - Year 2
- Undergraduate Mathematics,Operational Research,Statistics and Economics (Y602) - Year 2
- Undergraduate Discrete Mathematics (G4G1) - Year 2
- Undergraduate Discrete Mathematics (G4G3) - Year 2
- Undergraduate Mathematics and Economics (GL11) - Year 3
- Undergraduate Mathematics and Economics (with Intercalated Year) (GL12) - Year 4