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| STAT1218-1 | Statistical methods for economics
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| Duration : | 12h Th, 12h Pr |
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| Number of credits : |
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| Lecturer : | Yves Brostaux |
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Language(s) of instruction :
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| French language |
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Organisation and examination :
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| Teaching in the second semester |
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Course contents :
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| Descriptive statistics
- mesures of central location, dispersion, concentration
- index numbers
Time series
- decomposition methods
- smoothing methods
- ARIMA models |
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Learning outcomes of the course :
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| To learn statistical tools particularly useful to economics.
After completing the course the student is expected to
- summarize data from the field of business and social sciences,
- calculate index numbers,
- analyse univariate time series by various approches. |
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Prerequisites and co-requisites/ Recommended optional programme components :
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| Basic skills in applied statistics, for example :
- STAT1207-1- Applied statistics
Basic skills in computer science, for example :
- INFO2037-1- Introduction to computer science
- HULG0149-1- Office automation
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Planned learning activities and teaching methods :
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- Lectures and Q&A
- Exercises
- Personal work
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Mode of delivery (face-to-face ; distance-learning) :
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| Blended learning (face to face and e-learning) and flipped classrooms |
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Recommended or required readings :
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| - Syllabus and learning material on eCampus (mandatory)
- DAGNELIE P. [2007]. Statistique théorique et appliquée. Tome 1 : statistique descriptive et bases de l'inférence statistique. Bruxelles De Boeck, 511 p. (recommanded) |
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Assessment methods and criteria :
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| Oral examination (20%)
Personal reports (80%) |
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Work placement(s) :
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Organizational remarks :
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| Lectures : 8 h
Apart from the first introductory session, face-to-face sessions will be devoted to the presentation of the work to be done and questions and answers related to the theory and exercices. These sessions will be prepared beforehand on the basis of documents provided on eCampus, reading carefully the documents and resolving provided exercises .
These sessions will be devoted to an active discussion based on preparations and WILL NOT BE ex cathedra presentations of the material. To make the best of these face-to-face sessions, it is important to prepare them carefully BEFORE the class, which changes the paradigm of traditional lecture course.
Personal work
Three individual graded assignments will be given, one for each section of the course (Statistical parameters, Index numbers and time series), and will be transmitted via the eCampus platform. The instructions related to the completion of this work will be available in due time on eCampus and will be explained at face-to-face sessions.
In addition, ad hoc evaluations can be organized during the face-to-face sessions.
Organization
The detailed face sessions and the work schedule is available in the Planning section of the course of eCampus.
Participation in all educational activities organized is mandatory. |
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Contacts :
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| Yves Brostaux (Senior lecturer)
081 62 24 69
y.brostaux@ulg.ac.be |
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| Items online : |
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| eCampus |
| Supports de cours |
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