Objective:

• learning basic data processing techniques.

Content:

• 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.