MATS262 Probability Theory 2 (5 cr)

Open the course unit brochure on Sisu
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

* Types of convergence of random variables and measures
* Sums of independent random variables
* Convolution of probability measures
* Law of large numbers
* Central limit theorem

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

After the course

* the student knows the types of convergence of random variables and measures as well as their relations to each other,
* the student is familiar with the behaviour of sums of independent random variables, and knows the Law of large numbers and the Central limit theorem
* the student can identify (multidimensional) Gaussian distributions and describe their properties using characteristic functions

Description of prerequisites

MATS260 Probability theory 1

Study materials

Lecture notes: C. Geiss and S. Geiss: An Introduction to Probability Theory.

Completion methods

Method 1

Select all marked parts

Method 2

Select all marked parts
Parts of the completion methods
x

Teaching (5 cr)

Type:
Participation in teaching
Grading scale:
0-5
Language:
English

Teaching

x

Exam (5 cr)

Type:
Exam
Grading scale:
0-5
Language:
English

Teaching