Undergraduate Course: Statistical Consultancy (MATH10092)
|School||School of Mathematics
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 10 (Year 4 Undergraduate)
||Availability||Available to all students
|Summary||This course builds on the material on linear models for continuous response variables. More complex statistical models will be considered, such as, for example, models for repeated measures and non-linear regression models.
Students attend computer practical sessions in which they learn about the statistical language R, and use R to plot and summarise data sets, to fit models to data and draw appropriate conclusions. Statistical reports will be written describing the statistical methods applied and the corresponding conclusions that can be drawn, in the form of a consultancy report. Students are encouraged to confer on their analyses of the data, but their reports should be their own work.
Course for Honours Degrees involving Statistics. The syllabus will change from year to year according to what other courses in Statistics are offered, but examples of sample topics are:
1. Two-way and three-way classifications, blocking, interaction
2. Models with categorical and continuous variables, analysis of covariance
3. Generalized linear models for example for binary and count data
4. Repeated measures, emphasising the use of summary statistics
5. Random effect models
6. Non-linear regression
Information for Visiting Students
|High Demand Course?
Course Delivery Information
|Academic year 2018/19, Available to all students (SV1)
|Learning and Teaching activities (Further Info)
Lecture Hours 3,
Supervised Practical/Workshop/Studio Hours 12,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|No Exam Information
On completion of this course, the student will be able to:
- Choose and apply appropriate statistical models and methods for a range of statistical problems.
- Demonstrate a working practical knowledge of the statistical package R.
- Prepare typed reports of statistical analyses using LaTeX (or MS Word).
- Demonstrate experience of working on statistical consultancy-style projects.
|Venables, W. N. and Ripley, B. D., (2002). Modern Applied Statistics with S (4th edition). Springer.|
Crawley, M. J. (2012). The R Book (2nd edition). Wiley.
|Graduate Attributes and Skills
|Course organiser||Dr Bruce Worton
Tel: (0131 6)50 4884
|Course secretary||Mrs Alison Fairgrieve
Tel: (0131 6)50 5045