Statistics
Faculteit  Science and Engineering 
Jaar  2018/19 
Vakcode  WISTAT07 
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 about statistical estimation procedures, such as maximum likelihood estimation, and understand their properties; • the student are able to apply these procedures to a variety of settings. The student is able to: 1. apply estimation procedures; 2. show proof for CramerRao lower bound 3. derive properties, such as bias, consistency, sufficiency, efficiency, of estimation procedures; 4. derive and apply maximum likelihood estimation; 5. apply hypothesis testing and derive its properties; 6. show the proof of the NeymanPearson lemma; 7. apply estimation and testing principles to linear regression. 

Omschrijving  Up till now in your academic career, you might have calculated a probability of some event, given some known state of the world (i.e. the probability distribution). However, in practice we are often more interested to learn about the state of the world, given some event (i.e. the data). Statistics, therefore, is probability theory turned upside down. In this course we will learn about “estimation” procedures, in particular maximum likelihood, and some of their theoretical properties. We also learn about hypothesis testing. Then we apply both estimation and testing to a practical setting: linear regression analysis. This course picks up where the 1st year course Probability has finished: It is assumed known that students know the basic probability theory, including mean, variance and standard distributions such as the binomial, normal, Poisson etc. Also the basis of conditional probability is assumed known, including conditional mean and variance. The Central Limit Theorem and ideas about convergence in probability are crucial to evaluate the quality of a statistical procedure. 

Uren per week  
Onderwijsvorm  Hoorcollege (LC), Opdracht (ASM), Werkcollege (T)  
Toetsvorm 
Opdracht (AST), Schriftelijk tentamen (WE)
(The final grade (FG) is determined as follows: FG = 0.7 x WE + 0.1 x max{WE,HW1} + 0.1 x max{WE,HW2} + 0.1 x max{WE,HW3}, with WE grade of Written Exam and HWi grade of ith homework assignment.) 

Vaksoort  bachelor  
Coördinator  dr. M.A. Grzegorczyk  
Docent(en)  dr. M.A. Grzegorczyk  
Verplichte literatuur 


Entreevoorwaarden  The course unit assumes prior knowledge acquired from Calculus 1 and Probability Theory.  
Opmerkingen  the course prepares for Statistical modelling  
Opgenomen in 
