PSK 222 - Statistical Methods in Psychology II

The primary objective of this course is to provide psychology students with the basic and intermediate level of statistical analysis competence necessary to address research questions in the social sciences. By the end of the course, students will be able to translate a research problem into statistical hypotheses, select the most appropriate analytical technique (parametric or nonparametric) for the data structure and research design, apply these analyses using relevant software, and interpret and report the findings meaningfully within the context of the psychological literature. This course aims to develop students not only as statistical practitioners but also as competent researchers who can critically read scientific literature and construct their own research on solid methodological foundations.
 

The course begins with frequency analysis and chi-square tests used to analyze categorical data. It then covers parametric tests for examining differences between groups, including Independent and Dependent Groups t-Tests, One-Way ANOVA, and advanced ANCOVA and MANOVA. Nonparametric alternatives such as the Mann-Whitney U and Kruskal-Wallis H are also examined for cases where the parametric assumptions of these tests are not met. The course then focuses on Pearson and Spearman Correlation tests, as well as Simple and Multiple Linear Regression analyses, for analyzing relationships and predictive power between variables. From a psychometric perspective, it introduces Reliability and Validity analyses, which play a critical role in assessing the quality of measurement instruments, and Factor Analysis, which aims to simplify data structure. The course concludes with an introduction to alternative statistical software programs such as Jamovi, AMOS, and R, to put theoretical knowledge into practice.