Statistics
Faculteit  Science and Engineering 
Jaar  2020/21 
Vakcode  WBAI04905 
Vaknaam  Statistics 
Niveau(s)  bachelor 
Voertaal  Engels 
Periode  semester I a 
ECTS  5 
Rooster  rooster.rug.nl 
Uitgebreide vaknaam  Statistics  
Leerdoelen  The aim of the course is that  the students learn to reason from a statistical point of view;  the students learn how to implement various statistical test to solve practical datadriven problems;  the students learn the first principles of a linear and logistic regression model;  the students learn how to programme simulation and analysis methods in R. The student is able  to formulate a real problem in terms of quantitative measurable outcomes;  to explore the data from an applied problem in terms of descriptive statistics and/or visualizations in R;  to formally analyze the data using a variety of statistical tools, such as hypothesis tests, confidence intervals, linear regression, logistic regression and ANCOVA in R;  to interpret and critically discuss the results of the formal analysis;  to programme stochastic simulations in R. 

Omschrijving  Statistics is about extracting meaning from data. In this class, we will introduce techniques for visualizing relationships in data and systematic techniques for understanding these relationships. The course will make use of the R programming environment to analyze the data and will be encouraged to use R to implement stochastic simulations.  
Uren per week  
Onderwijsvorm 
Hoorcollege (LC), Opdracht (ASM), Practisch werk (PRC)
(4 hours lectures, 4 hours computer labs) 

Toetsvorm 
Opdracht (AST), Practisch werk (PR), Schriftelijk tentamen (WE)
(There will be 3 obligatory homework assignments. The final grade = (0.2 HW1 + 0.2 HW2 + 0.2 HW3 + 0.4 CE) if CE >= 5 and else finale grade = CE, where HWi is grade of ith homework assignment and CE grade of (computer) exam which will involve practical Rbased exercises as well as theoretical questions. The mark for the final exam should be larger or equal to 5.0 to pass the course.) 

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


Entreevoorwaarden  No prior knowledge is assumed.  
Opmerkingen  This course unit constitutes compulsory prior knowledge for the Bachelor’s Project for Artificial Intelligence students. This course was registered last year with course code WISTAKI07. 

Opgenomen in 
