| Course Title | Code | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|
| - | BESÖ504 | 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 | |
| Instructor(s) | |
| Assistants | |
| Goals | Determination and evaluation of data analysis in sports, technical-tactical competition analysis, systematic competition analysis method with video, analysis methods in training and competitions with the help of video and computer, the effect of coaches and athletes on their success, measurement and evaluation of motoric characteristics and their use. introduction to computer hardware, text processing, computer-aided data collection, statistical software and programming. |
| Course Content | The concept of data analysis in sport, The use of data analysis in sport, Competition analysis, Data analysis methods in sport, Data analysis of data topics constitute the content of this course. |
| Learning Outcomes |
- Explains basic information about data analyses in sport - The use of data analyses in sport, technical-tactical aspects of competition analysis, explains the connection - Provides computer-aided data collection related to the measurement, evaluation and utilisation of motoric characteristics in sport - Uses computer programmes related to data analysis effectively |
| Week | Topics | Learning Methods |
|---|---|---|
| 1. Week | General concepts related to data analyses in sport | |
| 2. Week | Identification and evaluation of data analyses and their use in sport | |
| 3. Week | Competition analysis from technical-tactical point of view | |
| 4. Week | Systematic competition analysis method with video, video and computer aided analysis methods in training and competitions | |
| 5. Week | The effect of data analysis methods on the success of coaches and athletes in sport | |
| 6. Week | Measurement and evaluation of motoric characteristics by data analysis method and its use | |
| 7. Week | Introduction to computer hardware, text processing, computer aided data collection, | |
| 8. Week | Mid-term exam | |
| 9. Week | Preparation of data for analysis Selection of sampling technique, Sample calculation | |
| 10. Week | Preparation of data for analysis and Data entry and data organisation - Selection of appropriate analysis technique | |
| 11. Week | Data entry and data organisation - Selection of appropriate analysis technique | |
| 12. Week | Data analysis Parametric fit tests Association-relationship measures Comparison of unrelated measures | |
| 13. Week | Data analysis Comparison of related measures (paired sample t test, ANOVA for repeated measures,) Comparison of mixed measures (Two Way ANOVA for mixed measures) | |
| 14. Week | Association-relationship Comparison of unrelated measures (independent sample t test, One Way Anova, Two Way Anova,) Comparison of related measures | |
| 15. Week | Final Exam |
| Ramazan baştürk (2011 ). Bütün yönleriyle spss örnekli nonparametrik istatistiksel yöntemler, 2. baskı anı yayıncılık Ankara |
| Hüsnü arıcı (2005). İstatistik yöntem ve uygulamalar 15 baskı pegem yayınları ankara |
| Yılmaz Kaya ( 2007).veri tabanı uygulamaları 2. baskı papatya yayıncılık Ankara |
| Erdoğan Gavcar (2009) istatistiksel yöntemler 1, gazi yayınevi, Ankara. |
| Program Requirements | Contribution Level | DK1 | DK2 | DK3 | DK4 | Measurement Method |
|---|---|---|---|---|---|---|
| PY5 | 5 | 5 | 5 | 5 | 5 | 40,60 |
| 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 |
