Probability & Statistics
People
Description
The class provides an introduction to probability theory, descriptive statistics (data exploration and graphical inference; measures of central tendency, dispersion, and correlation; simple and multiple linear regression), and inferential statistics (sampling distributions, confidence intervals, hypothesis testing). Theoretical concepts in the course will be illustrated with real-life examples and datasets, which students will analyse using the R software environment.
REFERENCES
- William Feller: An introduction to probability theory and its applications. J. Wiley, 1968-1971.
- Steven J. Miller: The Probability Lifesaver. Princeton University Press, 2017.
- Darrell Huff: How to lie with statistics. W.W. Norton & Co, 1954.
- Hogg, Tanis, Zimmerman: Probability and Statistical Inference, Ninth Edition. Pearson, 2015.
Education
- Bachelor of Science in Informatics, Core course, Lecture, 2nd year
- Master of Science in Management and Informatics, Management track, Lecture, 1st year
