Rapor Tarihi: 11.04.2026 04:50
| Course Title | Code | Language | Type | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|---|---|
| Applied Educational Statistics | EYD503 | Turkish | Compulsory | 3 + 1 | 4.0 | 6.0 |
| Prerequisite Courses | |
| Course Level | Graduate |
| Mode of delivery | Face to face |
| Course Coordinator | Doç. Dr. Taner ATMACA |
| Instructor(s) | Doç. Dr. Taner ATMACA (Güz) |
| Goals | The aim of this course is to enable graduate students to learn and apply fundamental statistical analysis methods used in educational research. Students will conduct analyses on real datasets, interpret results, and report findings professionally. The course integrates both the theoretical foundations of statistical techniques and their software-based applications. |
| Course Content | This course covers fundamental educational statistics techniques, including descriptive statistics, normality tests, correlation, t-tests, analysis of variance, regression analysis, non-parametric tests, and the use of statistical software (SPSS, JASP, or R). Students will engage in hands-on practice involving data cleaning, conducting analyses, and reporting results. |
| # | Öğrenme Kazanımı |
| 1 | |
| 2 | |
| 3 |
| Week | Topics/Applications | Method |
|---|---|---|
| 1. Week | Introduction to educational statistics; variable types and levels of measurement | Preparation, After Class Study, Research |
| 2. Week | Descriptive statistics: mean, variance, standard deviation, visualization | Preparation, After Class Study, Research |
| 3. Week | Normality testing, outlier analysis, and data cleaning | Preparation, After Class Study, Research |
| 4. Week | Correlation analysis and interpretation | Preparation, After Class Study, Research |
| 5. Week | Independent and paired samples t-tests | |
| 6. Week | One-way ANOVA and post-hoc procedures | Preparation, After Class Study, Research |
| 7. Week | Introduction to non-parametric tests (Mann-Whitney, Wilcoxon, Kruskal-Wallis) | Preparation, After Class Study, Research |
| 8. Week | One-way ANOVA and post-hoc procedures | Preparation, After Class Study, Research |
| 9. Week | Simple linear regression | Preparation, After Class Study, Research |
| 10. Week | Multiple regression and model comparison | Preparation, After Class Study, Research |
| 11. Week | Categorical data analysis (Chi-square tests) | Preparation, After Class Study, Research |
| 12. Week | Effect size and power analysis | Preparation, After Class Study, Research |
| 13. Week | Software-based analysis practice: SPSS / JASP / R | Preparation, After Class Study, Research |
| 14. Week | Student analysis presentations and final evaluation | Preparation, After Class Study, Research |
| No | Program Requirements | Level of Contribution | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | In order to graduate from the NON - THESIS MASTER'S program IN EDUCATIONAL ADMINISTRATION AND SUPERVISION, it is required to successfully complete 21 ECTS courses and a project. | ✔ | |||||
| Program Requirements | DK1 |
|---|---|
| PY1 | 3 |
| Ders Kitabı veya Notu | Ders Kitabı veya Ders Notu bulunmamaktadır. |
|---|---|
| Diğer Kaynaklar |
|
| ECTS credits and course workload | Quantity | Duration (Hour) | Total Workload (Hour) | |
|---|---|---|---|---|
|
Ders İçi |
Class Hours | 1 | 3 | 3 |
|
Ders Dışı |
Homework | 1 | 1 | 1 |
| Practice | 1 | 1 | 1 | |
|
Sınavlar |
Final | 1 | 3 | 3 |
| Total Workload | 8 | |||
| *AKTS = (Total Workload) / 25,5 | ECTS Credit of the Course | 6.0 | ||
