Syllabus
1.-2. Intro to software SPSS.
3. Exploratory data analysis, requirements of statical tests (normality, homoscedasticity, Levene test, Kolmogorov-Smirnov test, Q-Q diagram). Dependent and independent samples.
4. T-test - one-sample and two samples (equal and unequal varinces).
5. Paired t-test. Nonparametric tests-Sign test, median test, Mann-Whitney and Wilcoxon test.
6. Analysis of variance. Requirements and robustness. Between and within gropus variance. Test about equality of means.
7. Multile comparisons, contrasts and post hoc tests (equal and unequal varinces). More factors in ANOVA.
8. Kruskal Wallis test. Post hoc tests. (Friedman test).
9. Spearman and Kendall coefficient. Statistical methods for ordinal variables.
10. Chi-square test for frequency. Binomial test. Mc Nemar test.
11. Contingency tables. Count, total, row, column percentages. Pearson Chi-square test.
12. Contingency coefficients. Adjusted reziduals and sign scheme.
Annotation
Course is focused on basic statistical methods for social science data.