# Probability and Statistics 2 STA500

Basic issues in probability. Presentation of a number of commonly used probability distributions. Short introduction to extreme-value statistic. Estimation, in particular the maximum likelihood principle,and confidence intervals in various situations. Brief introduction to Bayesian statistics. Introduction to stochastic processes, in particular Poisson processes and Markov processes. Theory and areas for applications of the various methods will be covered.

Course description for study year 2021-2022. Please note that changes may occur.

Facts
Course code

STA500

Version

1

Credits (ECTS)

10

Semester tution start

Autumn

Number of semesters

1

Exam semester

Autumn

Language of instruction

English

Offered by

Faculty of Science and Technology, Department of Mathematics and Physics

Time table
Learning outcome
After having completed the course one should:
• Be able to use various probability distributions
• Have basic knowledge of extreme value statistics.
• Know about maximum likelihood estimation and have basic knowledge about estimation and confidence intervals
• Have basic knowledge of Bayesian statistics
• Know of common models for stochastic processes.
• Be able to do basic calculations for Poisson processes and Markov processes, including simple queue models.
Content
Basic issues in probability. Presentation of a number of commonly used probability distributions. Short introduction to extreme-value statistic. Estimation, in particular the maximum likelihood principle,and confidence intervals in various situations. Brief introduction to Bayesian statistics.Stochastic processes, in particular Poisson processes and Markov processes. Theory and areas for applications of the various methods will be covered.
Required prerequisite knowledge
None
Recommended prerequisites
MAT100 Mathematical Methods 1, MAT200 Mathematical Methods 2, MAT210 Real and Complex Calculus, STA100 Probability and Statistics 1
Exam

Coursework requirements
Mandatory submissions
At least 8 out of 12 exercises must be submitted and recieve a pass in order to be eligable to take the exam.
Course teacher(s)
Course coordinator: Jörn Schulz