Objective: learning basic data processing techniques. Topics:
- Data management.
- Descriptive statistics: sorting data, description of variables, description of the character and structure of population basing on a sample.
- Frequency tables: construction and description, frequency table as an empirical distribution.
- Statistical distributions: normal distribution, t-Student distribution, chi-squared distribution, Fisher-Snedecor distribution, parameters of distribution.
- Techniques of statistical inference: statistical hypotheses, statistical significance, accepting and rejecting the null hypothesis
- Parametric significance tests for two variables: t- Student tests for two independent samples and two related samples, z test, Fisher-Snedecor test for two samples.
- Chi-squared tests: goodness-of-fit test, test of association between variables.
Requirements: Students should have a computer with Microsoft.
