Rapor Tarihi: 11.04.2026 22:06
| Course Title | Code | Language | Type | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|---|---|
| Research Methods I | SSG501 | Turkish | Compulsory | 3 + 0 | 3.0 | 9.0 |
| Prerequisite Courses | |
| Course Level | Graduate |
| Mode of delivery | Expression and Practice |
| Course Coordinator | Dr. Öğr. Üyesi Abdulaziz SEZER |
| Instructor(s) | Dr. Öğr. Üyesi Abdulaziz SEZER (Güz) |
| Goals | The aim of this course is to provide students with knowledge of statistical research techniques and to enable them to apply these techniques in practice within the context of scientific research and academic writing. |
| Course Content | This course examines science and its fundamental concepts (such as fact, knowledge, absolute truth, error, and universal knowledge) and introduces basic information about the history of science. It addresses the structure of scientific research, scientific methods, and different perspectives on these methods. The course explains the identification of research problems, research designs, and the concepts of population and sample. It also covers data collection processes and data collection methods, including quantitative and qualitative techniques. In addition, the course focuses on the recording, analysis, interpretation, and reporting of research data within the framework of scientific research. |
| # | Öğrenme Kazanımı |
| 1 | Understands the fundamental concepts related to scientific research, learns the process and characteristics of scientific research. |
| 2 | Recognises statistical methods used in scientific studies in the field of business administration. |
| 3 | Applies and interprets basic statistical methods for conducting scientific research. |
| Week | Topics/Applications | Method |
|---|---|---|
| 1. Week | Theory, hypothesis, and other fundamental concepts in scientific research | Preparation, After Class Study |
| 2. Week | The scientific research process, its types and characteristics | Preparation, After Class Study |
| 3. Week | The concept of variables, measurement levels and scales | Preparation, After Class Study |
| 4. Week | Sampling theory and types | Preparation, After Class Study |
| 5. Week | Data collection and data measurement methods | Preparation, After Class Study |
| 6. Week | Survey application from cross-sectional data collection methods | Preparation, After Class Study |
| 7. Week | Data entry in SPSS, calculation of basic statistics | Presentation (Preparation), Practice, Preparation, After Class Study |
| 8. Week | Frequency analysis and creation of tables | Presentation (Preparation), Practice, Preparation, After Class Study |
| 9. Week | Reliability analysis, normality test | Preparation, After Class Study |
| 10. Week | Basic Components and Factor Analysis | Preparation, After Class Study |
| 11. Week | Hypothesis test analyses (One-tailed t-test, independent samples t-test, paired samples t-test) | Preparation, After Class Study |
| 12. Week | Hypothesis test analyses (One-way analysis of variance - ANOVA) | Preparation, After Class Study |
| 13. Week | Correlation analysis applications | Preparation, After Class Study |
| 14. Week | Regression analysis applications | Preparation, After Class Study |
| No | Program Requirements | Level of Contribution | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | In-depth Knowledge in Insurance and Social Security | ||||||
| 7 | Acquiring Research and Reporting Skills | ✔ | |||||
| Program Requirements | DK1 | DK2 | DK3 |
|---|---|---|---|
| PY1 | 10 | 10 | 10 |
| PY7 | 5 | 5 | 5 |
| 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 | 14 | 3 | 42 |
|
Ders Dışı |
Preparation, After Class Study | 14 | 3 | 42 |
| Research | 14 | 3 | 42 | |
| Other Activities | 14 | 3 | 42 | |
|
Sınavlar |
Midterm | 1 | 20 | 20 |
| Homework | 1 | 21.5 | 21.5 | |
| Final | 1 | 20 | 20 | |
| Total Workload | 229.5 | |||
| *AKTS = (Total Workload) / 25,5 | ECTS Credit of the Course | 9.0 | ||
