Advanced Statistics
Faculteit  Gedrags en MaatschappijWetenschappen 
Jaar  2022/23 
Vakcode  GMMSGE23 
Vaknaam  Advanced Statistics 
Niveau(s)  master 
Voertaal  Engels 
Periode  semester I a 
ECTS  7.5 
Rooster  rooster.rug.nl 
Uitgebreide vaknaam  Advanced Statistics  
Leerdoelen  After the course, the students:  Are able to reason under uncertainty and can demonstrate statistical thinking.  Are familiar with various approaches to estimation and testing, including least squares, maximum likelihood and Bayesian inference.  Are familiar with the general linear model and the generalized linear model (GLM).  Determine which statistical model is most appropriate for a given empirical question.  Are able to perform all statistical analyses learned in this course and before using the software package R. 

Omschrijving  This course deals with a variety of statistical models. The underlying conceptual framework as well as their application will be discussed. Starting from basic techniques such as the ttest and linear regression, we study statistical inference in detail. Several techniques for estimation and hypothesis testing and for model comparison and validation will be discussed. The course covers a wide range of linear models, as well as the versatile class of generalized linear models. Special emphasis will be placed on Bayesian inference. An important part of the course concerns learning the statistical software package R. Advanced familiarity with R, to the extend that the student can perform all statistical techniques that are either assumed known (e.g., ANOVA) or treated in this course, using R is a learning objective. As R will also be used in followup statistical courses in this degree programme, proficiency in R is not only important for passing this course, but for successful completion of all quantitative parts of the curriculum. 

Uren per week  6  
Onderwijsvorm 
hoorcollege, practicum
(Hours per week: 8 (weeks 12), 4 (weeks 37)) 

Toetsvorm 
computeropdrachten, tentamen
(The course evaluation consists of two components: A written exam and a computer exam for R.) 

Vaksoort  master  
Coördinator  prof. dr. C.J. Albers  
Docent(en)  prof. dr. C.J. Albers ,prof. dr. D. van Ravenzwaaij  
Verplichte literatuur 


Entreevoorwaarden  A thorough and active understanding of multiple regression and ANOVA models is required.  
Opmerkingen  
Opgenomen in 
