Applied statistics
MATH-516 / 5 credits
Teacher: Mhalla Ep Marchand Linda
Language: English
Withdrawal: It is not allowed to withdraw from this subject after the registration deadline.
Summary
The course will provide an overview of everyday challenges in applied statistics through case studies. Students will learn how to use core statistical methods and their extensions, and will use computational and problem-solving tools to provide reproducible solutions for the problems presented.
Content
The course will be problem-based, but solutions to the problems may require ideas and tools from areas such as smoothing, regression analysis, statistical modelling (likelihood methods) and model selection, time series analysis, spatial and functional data analysis, extreme value analysis, causal discovery, and statistical consulting.
Keywords
Causal discovery. Classification methods. Extreme value models. Model selection. Parametric and non-parametric regression models. Time series.
Learning Prerequisites
Required courses
Regression Methods, Statistical Computation and Visualisation.
Recommended courses
Time series, Statistical Inference.
Learning Outcomes
By the end of the course, the student must be able to:
- Propose suitable statistical solutions for real-world problems
- Apply suitable statistical solutions for real-world problems
- Assess / Evaluate the adequacy of a statistical method for a given task
- Report results clearly in writing and orally to different types of stakeholder
Transversal skills
- Give feedback (critique) in an appropriate fashion.
- Take feedback (critique) and respond in an appropriate manner.
- Communicate effectively with professionals from other disciplines.
- Access and evaluate appropriate sources of information.
- Write a scientific or technical report.
Teaching methods
One hour of lectures per week, plus three hours of work on mini-projects.
Expected student activities
Students will work on several mini-projects.
Assessment methods
Contrôle continu
Dans le cas de l'art. 3 al. 5 du Règlement de section, l'enseignant décide de la forme de l'examen qu'il communique aux étudiants concernés.
Supervision
| Office hours | No |
| Assistants | Yes |
| Forum | No |
In the programs
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Applied statistics
- Courses: 1 Hour(s) per week x 14 weeks
- Exercises: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Applied statistics
- Courses: 1 Hour(s) per week x 14 weeks
- Exercises: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Applied statistics
- Courses: 1 Hour(s) per week x 14 weeks
- Exercises: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Applied statistics
- Courses: 1 Hour(s) per week x 14 weeks
- Exercises: 3 Hour(s) per week x 14 weeks
- Type: mandatory
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Applied statistics
- Courses: 1 Hour(s) per week x 14 weeks
- Exercises: 3 Hour(s) per week x 14 weeks
- Type: mandatory