Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Institute of Graduate Programmes
  • Department of Physical Education and Sports
  • Physical Education and Sports (DR)
  • Course Structure Diagram with Credits
  • Quantitative Methods in Sport Psychology
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications
  • ECTS Credit Load

Course Introduction Information
Code - Course Title BES6503 - Quantitative Methods in Sport Psychology
Course Type Elective Courses
Language of Instruction Türkçe
Laboratory + Practice 3+0
ECTS 7.5
Course Instructor(s) DOKTOR ÖĞRETİM ÜYESİ UMUT SEZER
Mode of Delivery Face to face
Prerequisites
Courses Recomended
Required or Recommended Resources Beaujean, A. A. (2014). Latent variable modeling using R: A step-by-step guide. Routledge.Silva, B. C., Bosancianu, C. M., & Littvay, L. (2019). Multilevel structural equation modeling. Sage Publications.Gana, K., & Broc, G. (2019). Structural equation modeling with lavaan. John Wiley & Sons.Grimm, K. J., Ram, N., & Estabrook, R. (2016). Growth modeling: Structural equation and multilevel modeling approaches. Guilford Publications.Yu, Q., & Li, B. (2022). Statistical methods for mediation, confounding and moderation analysis using R and SAS. Chapman and Hall/CRC.
Recommended Reading List Morin, A. J., Myers, N. D., & Lee, S. (2020). Modern factor analytic techniques: Bifactor models, exploratory structural equation modeling (ESEM), and bifactor‐ESEM. Handbook of sport psychology, 1044-1073.
Assessment methods and criteria Midterm, Final
Work Placement
Sustainability Development Goals

Content

Weeks Topics
Week - 1 Introduction to R: RStudio and packages
Week - 2 Factor Analytic Models I: Unidimensional factor model, Correlated factors model
Week - 3 Factor Analytic Models II: Bifactor model, Hierarchical factor model
Week - 4 Multilevel Modeling I: Data structure, Fundamentals of hierarchical linear modeling
Week - 5 Multilevel Modeling II: Multilevel structural equation modeling
Week - 6 Multilevel Modeling III: Multilevel modeling for repeated measures
Week - 7 Multilevel Modeling IV: Mixed-effects model
Week - 8 Longitudinal Methods I: Time-lagged models
Week - 9 Longitudinal Methods II: Dynamic structural equation modeling
Week - 10 Actor-Partner Interdependence Model
Week - 11 Latent Profile Analysis
Week - 12 Social Network Analysis
Week - 13 Project I
Week - 14 Project II

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Observation
  • Team/Group Work
  • Drill - Practise
  • Case Study
  • Problem Solving
  • Brain Storming
  • Report Preparation and/or Presentation
  • Proje Design/Management
  • Competences
  • Productive
  • Rational
  • Questoning
  • Entrepreneur
  • Creative
  • Follow ethical and moral rules
  • Effective use of Turkish
  • Effective use of a foreign language
  • Work in teams
  • Use time effectively
  • Eleştirel düşünebilme
  • Abstract analysis and synthesis
  • Problem solving
  • Applying theoretical knowledge into practice
  • Information Management
  • Decision making

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%) 0
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