Methods of data analysis in scientific papers WF-PS-N-MAD

1. Repetition of basic information about the research process in psychology
- research problem, research question, hypotheses
- directional and non-directional hypotheses
- null hypotheses and research hypotheses
- measuring scale and research hypothesis
- emphasis on diversity: relationships between variables and differences between groups

2. Structure of the study report. APA standards

3. Introduction to SPSS - discussion of program functionality and specifics of data entry:
- three types of SPSS files: database, report, commands
- SPSS database: variables (all functionalities), data, rows, columns
- creating variables and entering data into SPSS
- SPSS and other file formats (Excel, dat.)
- combining sets, division into subsets, selection of observations

4. Basic ways of creating indicators (mean, sum). Recoding variables

5. Description and presentation of data:
- frequency tables and charts,
- descriptive statistics (measures of central tendency, measures of dispersion, measures of shape of the distribution) and tests of distribution normality

6. Basics of statistical inference and its errors (repetition). Tests using the chi-square distribution (form of hypotheses - type of data - assumptions)
- cross tables (observed numbers and expected numbers)
- chi2

7. Student's t-tests (form of hypotheses - type of data - assumptions and methods of their verification) and their nonparametric equivalents (Welch, Wilcoxon, U-Mann-Whitney tests)

8. Analysis of variance (form of hypotheses - type of data - assumptions and methods of their verification):
- one-factor, one-dimensional analysis of variance
- post hoc tests (concept of main effect) and contrasts
- two-factor, one-dimensional analysis of variance (the concept of simple effects and interactions)

9. Relationships between variables: correlations and regressions (form of hypotheses - type of data - assumptions and methods of their verification)
- correlation: assumptions, charts
- r-Pearson, rho-Spearman, tau-Kendall correlation
- partial correlation
- statistical inference: significance and strength of the relationship
- regression analysis in relation to r-Pearson correlation, partial correlation
- regression analysis with one predictor and with multiple predictors

10. Measurement reliability and validity:
- Cronbach's alpha (internal consistency of the scale)
- exploratory factor analysis

11. Repetition and reporting of results in accordance with APA style (structure of the empirical report)