Duration
15h Th, 15h Pr
Number of credits
| Master in urban planning and territorial development, professional focus in post-industrial and rurban territories | 3 crédits |
Lecturer
Language(s) of instruction
French language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
In this course, the students will receive an introduction to basic concepts of statistical inference:
- Hypothesis testing with respect to means and proportions (1 sample t-test, 2 sample t-test, and their non-parametric alternatives
- Correlation tests/independence tests
- Anova / Kruskal-Wallis
- Regression techniques
Learning outcomes of the learning unit
The student will be able to interpret output from statistical packages (in terms of basic statistical inference, hypothesis testing, and regression modelling).
The student will be able to implement a series of statistical datasets and formulate the main conclusions in a report.
Prerequisite knowledge and skills
Planned learning activities and teaching methods
6 mixed theory/practice lectures of 3 hours
Since the theoretical concepts are immediately applied in the software package R, bring your laptop to the course is essential for the course
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Course materials and recommended or required readings
Platform(s) used for course materials:
- eCampus
Exam(s) in session
Any session
- In-person
written exam ( open-ended questions )
Written work / report
Further information:
The course evaluation exists in two parts:
- An individual project where the student uses statistical software to formulate an answer to different research questions (35%)
- A written (closed book) exam where the student needs to interpret statistical output (65%)
Work placement(s)
Organisational remarks and main changes to the course
Given that the lectures focus on the practical aspects of using R for basic hypothesis tests, the time available to cover theoretical concepts is very limited. Therefore, video capsules on the theoretical concepts will be made available for students wishing to explore these aspects further.
To ensure that students can effectively apply the techniques taught during the courses, the code snippets and outputs are made available in English. This also facilitates the retrieval of additional information and help online.
Contacts
- Prof. Dr. Mario Cools: mario.cools@uliege.be