ST211 Half Unit
This information is for the 2021/22 session.
Dr Sara Geneletti Inchauste
Dr Sara Geneletti
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.
This course cannot be taken with ST201 Statistical Models and Data Analysis.
Statistical data analysis in R covering the following topics: Simple and multiple linear regression, Model diagnostics, Detection of outliers, Multicollinearity, Introduction to GLMs
This course will be delivered through a combination of classes and lectures (both or either of which maybe held online) totalling a minimum of 30 hours across Lent Term. This course includes a reading week in Week 6 of Lent Term in which a the students work independently on a mini-project (no lectures).
Regular Moodle quizzes. .
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.
Project (55%) and project (35%) in the ST Week 2.
Coursework (10%) in the LT Week 6.
10%: A group work mini-project to be handed in at the end of reading week (LT week 8)
55%: A group work multiple linear regression project to be handed in by the second week of the ST
35%: An individual logistic regression project to be handed in at the same time as the group project in the second week of the ST.
Course selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Student performance results
(2018/19 - 2020/21 combined)
|Classification||% of students|
Important information in response to COVID-19
Please note that during 2021/22 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 differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching 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.
Total students 2020/21: 52
Average class size 2020/21: 14
Capped 2020/21: Yes (60)
Value: Half Unit
Personal development skills
- Problem solving
- Application of information skills
- Specialist skills