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
3/17–5/25/2025 Lectures
5/14–5/14/2025 Course Exam
x
Exam (5 cr)
Type:
Exam
Grading scale:
0-5
Language:
English