MATS260 Probability Theory 1 (5 cr)
Study level:
Advanced studies
Grading scale:
0-5
Language:
English
Responsible organisation:
Department of Mathematics and Statistics
Curriculum periods:
2017-2018, 2018-2019, 2019-2020
Description
Content
Basic concepts of probability:
* probability space
* independence of events
* random variables
* expectation and its basic properties
* independence of random variables
Completion methods
Course exam and exercises. Part of the exercises may be obligatory.
Final exam is an other option.
Assessment details
The grade is based on
a) the number of points in the course exam and possibly additional points from exercises
OR
b) the number of points in the final exam.
At least half of the points are needed to pass the course.
Learning outcomes
The students are familiar with the concept of probability spaces, random variables, and independence.
They are able to describe simple stochastic phenomena within this framework and know important distributions. The notion of expected values along with the main theorems about integration is understood as extension of the Riemann integral.
The students are able to compute expected values based on discrete distributions and the Lebesgue measure on the real line.
They are able to describe simple stochastic phenomena within this framework and know important distributions. The notion of expected values along with the main theorems about integration is understood as extension of the Riemann integral.
The students are able to compute expected values based on discrete distributions and the Lebesgue measure on the real line.
Description of prerequisites
MATA280 Foundations of stochastics or TILA121 Probability or TILA1200 Probability 1.
Study materials
Lecture notes: C. Geiss and S. Geiss. Introduction to Probability Theory I
Completion methods
Method 1
Select all marked parts
Method 2
Select all marked parts
Parts of the completion methods
x
Unpublished assessment item
x
Unpublished assessment item