The aim of this course is to familiarize students with basic statistical terms and processes, which can be used for data processing and data analysis. The second part of the course is devoted to probability and calculations with random events. Furthe r part is aimed to random variables, especially with normal distribution of continuous random variables. The last topics are mathematical statistics, random sampling and statistical induction (estimates, hypotheses testing) investigating mean values of normal and alternative distribution.

Knowledge: Student knows and is able to use basic principles of descriptive statistics – data classification and calculation of important values. Student knows basic statistical attributes of the dataset and is able to use principles of their evaluation with the help of statistical characteristics (location and variability evaluation, attributes and characteristics based on moments). Student is able to use basic principles od decision problems under the risk conditions. Student knows, how to work with distribution of discrete and continuous random variables. Student is able to use basic principles of statistical induction (point and interval estimation, hypotheses testing) based on normally distributed random variables. Student is able to explain results of evaluated characteristics.

Skills: Student is able to evaluate simple or interval data classification and to present the results in the form of the chart or table and to evaluate important dataset values. Student is able to calculate statistical characteristics of the dataset from classified or unclassified data and to explain the results. Student is able to solve the problems with random events and their probabilities. Student is able to make the charts of probability (density) and distribution functions of basic kinds of distribution of discrete and continuous random variables and to evaluate their location and variability characteristics. Student is able to solve the problems with normal distribution. Student is able to construct point and interval estimators of unknown parameters based on normal distribution. Student is able to solve and explain the results of various basic hypotheses tests of unknown parameters based on test criterion normality.

General qualification: Student has overview of the basic statistical principles. Student knows the meaning of probability, practically sure event and risk principles. Student is able to apply the random events probability knowledge in simple examples of statistical induction based on normality of random variables. Student is able to apply the knowledge in other courses of his field of study and by the bachelor work elaboration.