Probability & Statistics
Probability theory is a deductive science describing the axioms for calculating the probability of some event given some known state of the world. In the first part of the course, we define the probability axioms, introduce the concept of events, random variables, and probability distributions. In inductive practice we are interested to learn about the state of the world given some event, i.e., the data. Statistics is probability theory turned upside down. In this course we will learn about estimation procedures, in particular, maximum likelihood and the method of moments. We will introduce hypothesis testing and linear regression analysis.
- Learn about probability axioms and (conditional) probability distributions, including moments of random variables and Chebychev's inequality.
- Understand law of large numbers and central limit theorem
- Study estimation methods, such a method-of-moments and maximum likelihood, and ways to evaluate estimators
- Develop hypothesis testing
- Understand and apply linear regression
Combination of lectures and tutorials
- Bachelor of Science in Informatics, Lecture, 2nd year
- Master of Science in Management and Informatics, Lecture, 1st year