ST211 Half Unit
Applied Regression
This information is for the 2020/21 session.
Teacher responsible
Dr Nicholas Cron (Columbia House 5.13)
Availability
This course is compulsory on the BSc in Business Mathematics and Statistics and BSc in Mathematics, Statistics and Business. This course is available as an outside option to students on other programmes where regulations permit. This course is not available to General Course students.
Specifically the course is available to Accounting and Finance students who have taken ST102.
Pre-requisites
ST102
Course content
Statistical data analysis in R covering the following topics: Simple and multiple linear regression, Model diagnostics, Detection of outliers, Multicollinearity, Introduction to GLMs
Teaching
This course will be delivered through a combination of classes and lectures totalling a minimum of 30 hours across Lent Term. This year, some or all of this teaching may be delivered through a combination of virtual classes and flipped-lectures delivered as short online videos. This course includes a reading week in Week 6 of Lent Term.
Formative coursework
Regular Moodle quizzes. Regular take home exercises.
Indicative reading
1. Gelman and Hill, Data analysis Using Regression and Multilevel/Hierarchical models (CUP, 2007) First part.
2. Neter, J., Kutner, M., Nachtsheim, C. and Wasserman, W. Applied Linear Statistical Models, McGraw-Hill, Fourth Edition. (2004).
3. Abraham, B. Ledolter, J. Introduction to Regression Modelling, Thomson Brooks Cole. (2006).
4. S. Weisberg Applied Linear Regression, Wiley, 3rd edition. (2005)(intermediate).
5. Fox (2016) Applied Regression Analysis and Generalized Linear Models.
Assessment
Exam (50%, duration: 2 hours) in the summer exam period.
Project (50%) in the ST.
There will be a single project due at the beginning of the ST.
Student performance results
(2017/18 - 2019/20 combined)
| Classification | % of students |
|---|---|
| First | 38.1 |
| 2:1 | 27.4 |
| 2:2 | 23.9 |
| Third | 6.2 |
| Fail | 4.4 |
Important information in response to COVID-19
Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Key facts
Department: Statistics
Total students 2019/20: 52
Average class size 2019/20: 27
Capped 2019/20: Yes (54)
Value: Half Unit
Personal development skills
- Self-management
- Problem solving
- Application of information skills
- Specialist skills
