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Asymptotic Statistics (BSc)
| Faculteit | Science and Engineering |
| Jaar | 2021/22 |
| Vakcode | WBMA002-05 |
| Vaknaam | Asymptotic Statistics (BSc) |
| Niveau(s) | bachelor |
| Voertaal | Engels |
| Periode | semester I b |
| ECTS | 5 |
| Rooster | rooster.rug.nl |
| Uitgebreide vaknaam | Asymptotic Statistics (BSc) | ||||||||||||||||||||||||
| Leerdoelen | The student is able 1) to apply basic modes of convergence in probability problems 2) to derive, develop, and interpret maximum likelihood or minimum chi-square inference methods for a number of estimation problems 3) to apply Laws of Large Numbers and versions of the Central Limit Theorem 4) to determine necessary and sufficient conditions for consistent and efficient estimators for a wide scope of problems |
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| Omschrijving | In this course the properties of probabilistic modes of convergence and their partial converses are analyzed in detail. Three Laws of Large Numbers and two versions of the Central Limit Theorem are proven, discussed and illustrated. To obtain a wider scope of application of these theorems, we introduce the Slutsky and Delta theorems. This forms the mathematical basis of regularity assumptions making statistical estimation possible based on maximum likelihood and minimum chi-square. Throughout the course we provide examples as well as counter examples to deepen insight. |
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| Uren per week | |||||||||||||||||||||||||
| Onderwijsvorm | Hoorcollege (LC), Opdracht (ASM), Werkcollege (T) | ||||||||||||||||||||||||
| Toetsvorm |
Opdracht (AST), Schriftelijk tentamen (WE)
(Assessment takes place through homework assignments and written exam according to Final = 0.10 x max(HW1, ET) + 0.10 x max(HW2, ET) + 0.10 x max(HW3, ET) + 0.7 x ET only if ET>=5.0 otherwise Final = ET, where HWi is homework grade for ith homework set, ET final exam grade.) |
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| Vaksoort | bachelor | ||||||||||||||||||||||||
| Coördinator | dr. W.P. Krijnen | ||||||||||||||||||||||||
| Docent(en) | dr. W.P. Krijnen | ||||||||||||||||||||||||
| Verplichte literatuur |
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| Entreevoorwaarden | The course unit assumes prior knowledge acquired from Statistics (2 year). Measure and Integration is very handy especially in the first part of the course. | ||||||||||||||||||||||||
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| Opgenomen in |
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