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| STAT1216-1 | Linear models and statistical modelling
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| Duration : | 36h Pr, 36h Th |
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| Number of credits : |
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| Lecturer : | Rodolphe Palm |
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Language(s) of instruction :
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| French language |
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Course contents :
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| Linear regression
- simple and multiple regression
- variable selection
- examining residuals and checking assumptions
- weighted regression and variable transformation
Simple, multiple and partiel correlation
Comparison of two or several populations
Principal component regression and PLS
Ridge regression
Non linear regression
Logistic regression
Robust and non parametric regression |
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Learning outcomes of the course :
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| To revise and complete the basic elements of simple and multiple linear regression, to learn advanced statistical methods to model a response variable as a function of one or several predictors.
After completing the course the student is expected to
- model correctly the relationship between a dependent variable and one or several explanatory variables,
- check fitted models,
- compare models related to two or several populations. |
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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 :
-- HULG0149-1- Office automation
or -- INFO2037-1- Introduction to computer science |
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Planned learning activities and teaching methods :
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| Lectures
Exercises on computer |
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Mode of delivery (face-to-face ; distance-learning) :
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| Face-to-face |
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Recommended or required readings :
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| - Syllabus.
- Reference book : DRAPER N.R., SMITH H. [1998]. Applied regression analysis. New York, Wiley, 706 p. |
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Assessment methods and criteria :
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| Written examination (100%) |
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Organizational remarks :
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| Lectures : 36 h
Practical Works : 36 h |
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Contacts :
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| Palm, Rodolphe (Professeur)
Enseignement et recherche
081 62 24 79
Rodolphe.Palm@ulg.ac.be |
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