ST304 Half Unit
Time Series and Forecasting
This information is for the 2020/21 session.
Teacher responsible
Dr Yining Chen COL 5.08
Availability
This course is available on the BSc in Actuarial Science, BSc in Business Mathematics and Statistics, BSc in Mathematics with Economics and BSc in Mathematics, Statistics and Business. This course is available as an outside option to students on other programmes where regulations permit and to General Course students.
Pre-requisites
2nd year statistics and probability
Course content
The course introduces the student to the statistical analysis of time series data and simple models, and showcase what time series analysis can be useful for. Topics include: autocorrelation; stationarity, trend removal and seasonal adjustment, basic time series models; AR, MA, ARMA; invertibility; estimation; forecasting; introduction to financial time series and the GARCH models; unit root processes; basic spectral analysis. Some R demonstrations will also be included.
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
Written answers to set problems will be expected on a weekly basis.
Indicative reading
Peter J. Brockwell and Richard A. Davis, Introduction to Time Series and Forecasting
Christopher Chatfield, The Analysis of Time Series.
Robert H. Shumway, David S. Stoffer, Time Series Analysis and Its Applications: With R Examples
Ruey S. Tsay, An Introduction to Analysis of Financial Data with R
Assessment
Exam (100%, duration: 2 hours) in the summer exam period.
Student performance results
(2017/18 - 2019/20 combined)
Classification | % of students |
---|---|
First | 37.2 |
2:1 | 25.1 |
2:2 | 15 |
Third | 10.9 |
Fail | 11.7 |
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: 63
Average class size 2019/20: 21
Capped 2019/20: No
Value: Half Unit
Personal development skills
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills
- Commercial awareness
- Specialist skills