Statistics

- Basic terms and sizes: population and range, average, median, variance, standard deviation
- Graphic representations and presentation of statistical data
- Probability calculation: quantitative, conditional probability, independence and combinatorics
- Stochastic models notation, calculation of probability, expectation and variance of discrete and continuous models
- Probability Distributions: Theory and Practical Use of the Binomic and Hypergeometric Model, Poisson Distribution, Normal Distribution and Central Limit Theorem
- Statistical methods: determination of point estimators and confidence intervals and implementation of hypothesis tests with pendants in known models
- Comparison of groups with t-tests with formulas and on PC
- Implementation of Kji-kvadrattest and variance analysis on PC
- Analysis of correlation and linear regression correlation

It is expected that the student is able to:
- compute statistical goals for sample data and produce results in tables and graphics
- use notation for statistics regarding quantity, independence and conditional probability
- calculate probabilities with combination games for lotteries etc.
- explain common probability models and calculate probabilities
- interpret results of surveys with confidence intervals and p-values from hypothesis tests
- calculate confidence intervals and perform hypothesis tests on the basis of collected data and common probability models
- apply linear regression and evaluate the results of the analysis
- use computer programs for statistical calculations and analyzes

Lecture hours: 6
Practice hours: 4
Specialization hours: 4