Ability of abstract thinking and acquiring basic knowledge in the area of statistics.

Student is competent to design and solve mathematical models in the field of statistics in further education and professional courses.

Population, sample. Sampling techniques. Descriptive statistics, point estimate and interval estimate. Parametric and nonparametric hypotheses and significance testing. Statistical inference.

Lectures; Numerical computing practice. Consultations. Lectures are combined. In lectures, theoretical part of the course is followed by typical examples for better understanding. In practice, which accompanies lectures, typical problems are solved and knowledge from the lectures is deepened. Besides lectures and practice, consultations are held on a regular basis. Part of the course, presenting a logical whole, can be passed during the teaching process in the form of the following 2 modules (the first module: descriptive statistics, the second module: statistical hypothesis testing) . The oral part of the examination is not obligatory.