MATS262 Probability Theory 2 (5 cr)

Study level:
Advanced studies
Grading scale:
0-5
Language:
English, Finnish
Responsible organisation:
Department of Mathematics and Statistics
Curriculum periods:
2024-2025, 2025-2026, 2026-2027, 2027-2028

Description

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

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,
  • is familiar with the behavior of sums of independent random variables, and knows the Law of large numbers and the Central limit theorem
  • 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

Evaluation criteria:
The grade of the course is determined by the points aquired in the exam and in the exercises.
Time of teaching:
Period 4
Select all marked parts

Method 2

Evaluation criteria:
The grade of the course is determined by the points aquired in the exam.
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