Probability Theory
Faculteit  Science and Engineering 
Jaar  2017/18 
Vakcode  WIKR06 
Vaknaam  Probability Theory 
Niveau(s)  propedeuse 
Voertaal  Engels 
Periode  semester II b 
ECTS  5 
Rooster  rooster.rug.nl 
Uitgebreide vaknaam  Probability Theory  
Leerdoelen  After the course: 1. The student can reproduce basic concepts such as sample space and events in relation to axioms of probability such as the inclusionexclusion formula. 2. The student can solve basic combinatorial problems. 3. The student is able to translate experimental settings into probability density and cumulative distribution functions 4. The student can compute expectation and higher order moments either directly or by the momentgenerating function 5. The student is able to derive basic properties of several standard probability distributions such as the multivariate Gaussian. 6. The student is able to determine conditional distributions from a given joint distribution and to determine distributions as a transformation from a given distribution 7. The student can prove convergence in probability and in distribution from the Law of Large Numbers and the Central Limit Theorem The course contributes to the following transferable skills: 1. conducting mathematical proofs (more generally, scientific reasoning) 2. problem solving 

Omschrijving  Everyone has an intuitive idea of concepts such as “chance” and “opportunity”. We can for instance think of: a lottery, weather, stock prices, or the number of cars at a given time on a motorway. In this course we will formalize these ideas by defining “probability” as a mathematical object that satisfies certain axioms. The aim of this course is to train the student in using the formal mathematical framework to derive certain properties of various stochastic concepts. In particular, we build up a general space, in which probability is used as a measuring tool. We introduce concepts such as probability density and expectation and derive various limit theorems. On the other hand, we will see how our mathematical framework enables us to solve practical problems. In order to facilitate this, we will consider combinatorics and several standard probability densities. 

Uren per week  
Onderwijsvorm  Hoorcollege (LC), Werkcollege (T)  
Toetsvorm 
Opdracht (AST), Schriftelijk tentamen (WE)
(Assessed homework, written exam: Final = 0.1 x max(HW1, ET) + 0.1 x max(HW2, ET) + 0.1 x max(HW3, ET) + 0.7 x ET only if ET >=4.5 otherwise Final = ET, where HWi is homework grade for ith homework set, ET final exam grade.) 

Vaksoort  propedeuse  
Coördinator  prof. dr. T. Müller  
Docent(en)  prof. dr. T. Müller  
Verplichte literatuur 


Entreevoorwaarden  
Opmerkingen  
Opgenomen in 
