Topics

The seminar is structured in 10 main thematic sections:

1. Familiarity with the working environment of the program.
   This section is essentially the first introduction to the program. That is, the guidelines for managing the program options are given and the basic concepts and functions of the program are explained.
2. Data management in the program interface.
   This section introduces the use of the program’s toolbars in order to become familiar with database management.
3. Introduction to Statistics-Descriptive Statistics-Tables/Graphs.
   This section is an introduction to Statistics. Basic concepts of descriptive statistics are explained and the learner becomes familiar with presenting descriptive numerical measures using the program’s functions.
4. Analytical Statistics-Hypothesis Testing-Distribution Testing.
   In this module, the hypothesis testing process is taught as the basic stage of analytical statistics.
5. Quantitative data analysis – Testing of two-sample mean values ​​by Student’s t-test.
   The purpose of this section is to investigate the differences of quantitative variables in two groups.
6. Quantitative Data Analysis – Analysis of Variance (ANOVA).
   The purpose of this section is to investigate the differences of quantitative variables in more than two groups.
7. Non-parametric controls.
   In this section, statistical tests are taught when the appropriate conditions of their distributions are not met.
8. Correlation tests-X2, Pearson’s r, Spearman’s rho.
   This section describes the statistical tests for investigating associations.
9. Linear Regression.
   Creating models to investigate factors associated with the appearance of quantitative traits.
10. Logarithmic Regression.
    Building models to investigate factors associated with the emergence of binomial traits.