Faculteit  Science and Engineering 
Jaar  2018/19 
Vakcode  WBMA14003 
Vaknaam  Asymptotic Statistics (BSc) 
Niveau(s)  bachelor 
Voertaal  Engels 
Periode  semester I a 
ECTS  5 
Rooster  rooster.rug.nl 
Uitgebreide vaknaam  Asymptotic Statistics (BSc)  
Leerdoelen  The aim of the course is that students obtain insight on the role of asymptotic theory in statistical estimation theory. The student is able 1) to apply basic modes of convergence in probability problems 2) to derive, develop, and interpret maximum likelihood or minimum chisquare 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 

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 chisquare. Throughout the course we provide examples as well as counter examples to deepen insight. 

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, WE) + 0.10 x max(HW2, WE) + 0.10 x max(HW3, WE) + 0.7 x WE only if WE>=5.0 otherwise Final = WE, where HWi is homework grade for ith homework assignment, WE final exam grade) 

Vaksoort  bachelor  
Coördinator  dr. W.P. Krijnen  
Docent(en)  dr. W.P. Krijnen  
Verplichte literatuur 


Entreevoorwaarden  The course unit assumes prior knowledge acquired from Statistics (2 year).  
Opmerkingen  
Opgenomen in 
