| Course Title | Code | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|
| - | SYP503 | 3 + 0 | 3.0 | 9.0 |
| Prerequisites | None |
| Language of Instruction | Turkish |
| Course Level | Graduate |
| Course Type | |
| Mode of delivery | Face to face |
| Course Coordinator | |
| Instructors |
Reşat SADIK |
| Assistants | |
| Goals | It is an indispensable necessity to be able to make data analysis, which is an important stage of the scientific research process in Sports Sciences, correctly and in accordance with the requirements, and to be able to interpret the findings correctly. In addition, countless problems are encountered in the business world every day and these problems await solutions. As a result of the analysis of the obtained data, the problems can be solved. The aim of this course is to gain the ability to correctly obtain the data about the investigated event, to make it ready for analysis by passing through various filters, and to analyze and interpret the data with the most appropriate methods by using the SPSS (Statistical Packages for the Social Sciences) program. |
| Course Content | In this course, the concept of data and data recognition, statistical analyzes to be chosen in accordance with the purpose and in this context, descriptive statistics, tests for comparisons of two and/or more than two groups, non-parametric tests, correlation and regression analysis and factor from multivariate statistical analysis, clustering analysis are the subjects. will be processed. |
| Learning Outcomes |
- Recognizes the data that can be obtained in researches in terms of their characteristics, - Creates an appropriate data collection tool in a case under study. - Prepares the available data for analysis with appropriate methods in a case under investigation. |
| Week | Topics | Learning Methods |
|---|---|---|
| 1. Week | enterance | |
| 2. Week | Data Concept and Data Acquisition Methods | |
| 3. Week | Selection of Statistical Technique to be Used in Data Analysis | |
| 4. Week | Introduction to SPSS Package Program | |
| 5. Week | Data Operations in SPSS | |
| 6. Week | Data Operations in SPSS | |
| 7. Week | Descriptive Statistics | |
| 8. Week | Tests for Two-Group Comparison | |
| 9. Week | Analysis of Variance | |
| 10. Week | Non-Parametric Tests | |
| 11. Week | Non-Parametric Tests | |
| 12. Week | Linear Regression and Correlation Analysis | |
| 13. Week | Factor Analysis | |
| 14. Week | Cluster Analysis |
| Program Requirements | Contribution Level | DK1 | DK2 | DK3 | Measurement Method |
|---|
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| Course's Level of contribution | None | Very Low | Low | Fair | High | Very High |
| Method of assessment/evaluation | Written exam | Oral Exams | Assignment/Project | Laboratory work | Presentation/Seminar |
| Event | Quantity | Duration (Hour) | Total Workload (Hour) |
|---|---|---|---|
| Midterm 1 | 1 | 25 | 25 |
| Midterm 2 | 1 | 25 | 25 |
| Homework 1 | 1 | 10 | 10 |
| Homework 2 | 1 | 10 | 10 |
| Quiz 1 | 1 | 15 | 15 |
| Quiz 2 | 1 | 15 | 15 |
| Final | 1 | 44.5 | 44.5 |
| Practice | 1 | 30 | 30 |
| Practice End-Of-Term | 1 | 30 | 30 |
| Classroom Activities | 1 | 25 | 25 |
| Total Workload | 229.5 | ||
| ECTS Credit of the Course | 9.0 | ||
