- Introduction to descriptive statistics and basic terminology (means, spread, distribution, index, correlation, linear regression); - conditional probability; discrete random variable and distribution; continuous random variable and normal distribution; - inductive statistics (basics; test theory; tests in the context of various models; classic linear regression model, simple and multiple regression)
Project Management & IT (Bachelor)
Language of instruction
Upon successful completion, students will have acquired basic knowledge of statistical concepts and they will be able to apply them to diverse economic problems. Students will be able to explain and use basic analytical methods of descriptive statistics as well as the most important probability laws and relevant distribution laws. They will be able to calculate parameter estimates, test hypotheses and transfer a sample survey to the corresponding universe. They will be able to quantitatively analyse univariate and multivariate data sets.