Faculty of Humanities and Social Sciences · Psychology (English) · Undergraduate
Course Objective
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.
Course Content
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.
Required Resources
Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Wadsworth.
Recommended Resources
Kimberlin, C. L., & Winterstein, A. G. (2008). Validity and reliability of measurement instruments used in research. American journal of health-system pharmacy, 65(23), 2276-2284.;
George, D. ve Mallery, P. (2019). IBM SPSS statistics 23 step by step: A simple guide and reference (14. baskı). Routledge. https://doi.org/10.4324/9780429056765
Course Learning Outcomes
- Applies parametric tests such as t-test and ANOVA, and their non-parametric counterparts (Mann-Whitney U, Kruskal Wallis H), to test for mean differences between two or more groups.
- Uses correlation analyses to examine the direction and strength of the relationship between variables, and regression analyses to test the predictive power of one or more variables on another.
- Correctly interprets and reports key values from statistical analysis outputs (e.g., p-value, effect size, confidence interval) within the context of psychological science.
- Explains the importance and application logic of basic reliability and validity analyses to evaluate the psychometric properties of a measurement instrument.
- Defines the basic logic and purpose of factor analysis used to uncover latent structures in multivariate data sets.
- Performs basic data analysis steps (data entry, analysis, output interpretation) using at least one statistical software program such as Jamovi, AMOS, or R.
- Critically evaluates the appropriateness and validity of statistical methods and findings presented in scientific articles in the field of psychology.
Core Area Distribution
Teaching Methods
Assessment & Evaluation
ECTS / Workload
| Activity | Quantity | Duration (h) | Total Workload |
|---|---|---|---|
| Course Duration (Including Exam Week) | 16 | 3 | 48 |
| Out of Class Study Period | 16 | 6 | 96 |
| Midterm | 1 | 1 | 1 |
| Quiz | 0 | 0 | 0 |
| Assignment | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Final | 1 | 1 | 1 |
Course Schedule
| Week | Subject | Preparation |
|---|---|---|
| 1 | Frequency Analysis and Chi-Square Tests | Howell (2010) Chapter 6 |
| 2 | T-Test | Howell (2010) Chapter 7 |
| 3 | Mann-Whitney U Test | Howell (2010) Chapter 18 |
| 4 | ANOVA and Post Hoc Tests | Howell (2010) Chapter 11 |
| 5 | ANCOVA and MANOVA | Howell (2010) Chapter 11 |
| 6 | Kruskal Wallis H | Howell (2010) Chapter 18 |
| 7 | Pearson and Spearman Correlation Tests | Howell (2010) Chapter 9 |
| 8 | Midterm Exam Week | Course Slides |
| 9 | Simple Linear Regression Test | Howell (2010) Chapter 9 |
| 10 | Multiple Linear Regression Test I | Howell (2010) Chapter 15 |
| 11 | Multiple Linear Regression Test II | Howell (2010) Chapter 15 |
| 12 | Reliability and Validity Tests | Kimberlin & Winterstein (2008) |
| 13 | Introduction to Factor Analysis | Howell (2010) Chapter 13 |
| 14 | Alternative Statistical Applications: Jamovi, AMOS and R | Blanca et. al. (2018) |
| 15 | Statistics, Research Methods and Psychology | Course Slides |
| 16 | Final Exam Week | Course Slides |