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, significance testing). Theoretical concepts in the course will be illustrated with real-life examples and datasets, which students will analyse using the R software environment.
- Elements of information theory [Archivio elettronico] / Thomas M. Cover, Joy A. Thomas. - Hoboken, N.J. : Wiley-Interscience, 2006.
- An introduction to probability theory and its applications / William Feller. - New York [etc.] : J. Wiley, 1968-1971.
- Hogg, Tanis, Zimmerman: Probability and Statistical Inference, Ninth Edition (2015)
- Diez, Barr, Cetinkaya-Rundel: OpenIntro Statistics, Third edition (2017) https://www.openintro.org/stat/textbook.php?stat_book=os
- Darrell Huff: How to lie with statistics (1954)
- Lecture notes will be made available on the e-learning platform.