Required in stage
First term
Second term
Both terms
This year
Next year
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Prerequisites
Taught by
Language of instruction
Duration
LevelStatistical Modelling (B-KUL-D0N23A)
Cannot be taken as part of an examination contractAims
The students should get familiar with different models and model classes, know when to apply which type of model. Students should be able to understand and fit different types of models using the statistical software R, and to interpret the results.
Previous knowledge
Basic knowlodge of statistics and mathematics, knowlegde of statistical techniques, including the basic regression model.
Content
- Different types of model families (such as the general linear model, generalised linear model, non-linear model).
Estimation and inference inside such models.
- Application of model selection methods (forward, backward selection, AIC, BIC, Cp,
)
- Models with random effects (in linear, non-linear, generalised linear models)- Smoothing methods (such as additive models, single index models, partially linear models)
Course material
Syllabus
Toledo / e-platform
Is also included in other courses
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Master of Financial Economics
60 ects.
-
Master of Advanced Business Studies
60 ects.
Activities
3.0 ects. Statistical Modelling (B-KUL-G0A22a)
Content
- Different types of model families (such as the general linear model, generalised linear model, non-linear model).
Estimation and inference inside such models.
- Application of model selection methods (forward, backward selection, AIC, BIC, Cp,
)
- Models with random effects (in linear, non-linear, generalised linear models)- Smoothing methods (such as additive models, single index models, partially linear models)
Aims
The students should
get familiar with different models and model classes, know when to apply which type of
model. Students should be able to understand and fit different types of
models using statistical software, and to interpret the results.
Description of learning activities
The student is expected to actively participate to the courses. It is expected that the student applies the methodology using statistical software packages to obtain estimators, conduct inference, construct graphs, Practical exercises are important.
Course material
Cursustekst "Statistical Modelling" (G. Claeskens, Acco cursus)
Toledo
This course is also included in
Evaluation
Evaluation: Statistical Modelling (B-KUL-D2N23a)
Explanation
Determining exam results
* The exam is assessed by the lecturer(s), as communicated through Toledo and the examination schedule. The grade is expressed as an integer number between 0 en 20.
The exam of 'Statistical Modelling' constis of 2 assignments, each for 15 %, and the take-home project, for 70 %.
The deadline of the assignments and the take-home project is determined by the lecturer and communicated through Toledo. If the set deadline is not respected, the final grade of the course will be 0/20, unless the student requested the lecturer for a new deadline because of serious reasons.
Evaluation third examination period
* During the academic year, a student has 2 chances to participate to the exam: a first time during the first or second examination period, in accordance with the scheduled semester, and a second time during the third examination period.
* The evaluation criteria of the third examination period are identical to those of the first or second examination period.
