Study programme 2021-2022 | Français | ||
Statistical Data Analysis | |||
Programme component of Master's in Mathematics à la Faculty of Science |
Code | Type | Head of UE | Department’s contact details | Teacher(s) |
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US-M1-SCMATH-042-M | Optional UE | SIEBERT Xavier | F151 - Mathématique et Recherche opérationnelle |
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Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Credits | Weighting | Term |
---|---|---|---|---|---|---|---|---|---|
| Français | 18 | 18 | 0 | 0 | 0 | 4 | 4.00 | 1st term |
AA Code | Teaching Activity (AA) | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term | Weighting |
---|---|---|---|---|---|---|---|---|
I-MARO-014 | Data Mining | 18 | 18 | 0 | 0 | 0 | Q1 | 100.00% |
Programme component |
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Objectives of Programme's Learning Outcomes
Learning Outcomes of UE
- understand and explain the theory, models and techniques used
- identify which model(s) are best suited for a given dataset
- analyse datasets using a software
- interpret the results from the software, showing an understanding of the theory
Content of UE
- descriptive techniques such as principal components analysis and discriminant analysis
- classical models of statistical data analysis (analysis of variance, linear regression)
- data mining (classification and clustering)
Prior Experience
Elementary statistics
Algebra and Calculus
Type of Assessment for UE in Q1
Q1 UE Assessment Comments
written exam for the theory, practial exam on the computer
Type of Assessment for UE in Q3
Q3 UE Assessment Comments
idem Q1
Type of Resit Assessment for UE in Q1 (BAB1)
Q1 UE Resit Assessment Comments (BAB1)
Not applicable
Type of Teaching Activity/Activities
AA | Type of Teaching Activity/Activities |
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I-MARO-014 |
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Mode of delivery
AA | Mode of delivery |
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I-MARO-014 |
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Required Reading
AA | |
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I-MARO-014 |
Required Learning Resources/Tools
AA | Required Learning Resources/Tools |
---|---|
I-MARO-014 | - slides of oral presentations (theory and examples) - problem sets |
Recommended Reading
AA | |
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I-MARO-014 |
Recommended Learning Resources/Tools
AA | Recommended Learning Resources/Tools |
---|---|
I-MARO-014 | Sans objet |
Other Recommended Reading
AA | Other Recommended Reading |
---|---|
I-MARO-014 | R.O.Duda, P.E.Hart, D.G.Stork. "Pattern Classification". John Wiley and Sons, 2000. C.M. Bishop Pattern recognition and machine learning. springer, 2006. R.E.Walpole, R.H.Myers, S.L.Myers, K.Ye, "Probability and Statistics for Engineers and Scientists", Prentice Hall, 2012 K P Murphy, Machine learning: a probabilistic perspective. MIT press, 2012. |
Grade Deferrals of AAs from one year to the next
AA | Grade Deferrals of AAs from one year to the next |
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I-MARO-014 | Authorized |