Course Information


Course Information
Course Title Code Semester L+U Hour Credits ECTS
ADVANCED STATISTICS IN SPORTS SCIENCES 78141003 3 + 0 3.0 9.0

Prerequisites None

Language of Instruction Turkish
Course Level Graduate Degree
Course Type Compulsory
Mode of delivery Oral and visual presentation
Course Coordinator
Instructors Cengiz AKALAN
Assistants
Goals Sports science in examining in detail the frequently used statistical methods and analyze with the help of statistical analysis programs , the results and preparing reports
Course Content Sports science and social science planning the necessary statistical applications through a research design in the field , learning the application and interpretation techniques , apply using selected statistical analysis computer software package program and interpretation of statistical analysis to understand the use of methods and stages
Learning Outcomes 1) 1. Knowledge: Sport sciences and social sciences by making a planning application for the necessary statistics and research design in the field , learning the application and interpretation techniques
2) 2. Skills : To apply selected using statistical analysis and interpretation of the software package
3) 3. Attitude: To understand the use of statistical analysis methods and stages

Weekly Topics (Content)
Week Topics Teaching and Learning Methods and Techniques Study Materials
1. Week Introduction to statistics and hypothesis analysis Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
2. Week -Change The range of the normal distribution -Arithmetic mean- variance - standard error- confidence interval Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
3. Week Descriptive statistics - Percentage distribution of distributions -Group Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
4. Week -General research proposal preparation and reporting of Graphic preparation of the table Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
5. Week Average Comparisons - Average -One -sample T- test Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
6. Week Independent samples T- test Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
7. Week MID-TERM - Dependent Sample T Test Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
8. Week Dependent and independent samples T- test sample T- test results to create the table and report writing Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
9. Week Single and multi -way ANOVA analysis / identification of the different groups Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
10. Week Create a result table and report writing in single and multi -way ANOVA Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
11. Week Assays Correlation Correlation coefficient - Correlation matrix Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
12. Week Creating Correlation analysis of the results and report writing table Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
13. Week Regression analysis Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
14. Week Creating results table regression analysis and report writing Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)
15. Week General discussion and summary Lecture; Question Answer
Brainstorming; Six Hats Thinking
Project Based Learning; Problem Based Learning 		Homework Presentation (Including Preparation Time)

Sources Used in This Course
Recommended Sources
İstatistik ve spor Bilimleri. Alpar.R.Bağırgan yayın., Ankara (2004)
Satistical Reasoning For The Behavioral Sciences. Shavelson, R.J. Allyn&Bacon. USA (2006)
The Basic Practice of Statistics. Moore, D.S. Freeman. USA.(2005)

Relations with Education Attainment Program Course Competencies
Program RequirementsContribution LevelDK1DK2DK3
PY15000
PY25000
PY35000
PY45000

*DK = Course's Contrubution.
0 1 2 3 4 5
Level of contribution None Very Low Low Fair High Very High
.

ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
Course Duration (Total weeks*Hours per week) 15 5
Homework 5 20
Report (Including Preparation and presentation Time) 3 6
Practice (Teaching Practice, Music/Musical Instrument Practice , Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice) 3 3
Seminar 2 5
Quiz 3 3
Midterm Exam 1 2
Time to prepare for Final Exam 1 3
2 2
1 1
4 8
2 6
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course
Quick Access Hızlı Erişim Genişlet
Course Information
  • Course Information
  • Weekly Topics (Content)
  • Sources Used in This Course
  • Relations with Education Attainment Program Course Competencies
  • ECTS credits and course workload