Nevşehir Hacı Bektaş Veli University Course Catalogue

Information Of Programmes

INSTITUTE OF SOCIAL SCIENCES / ANE-102 - ANTRENöRLüK EğITIMI ANABILIM DALı YüKSEK LISANS (ÖNERILEN)

Code: ANE-102 Course Title: STATISTICS IN SPORTS SCIENCES Theoretical+Practice: 3+0 ECTS: 5
Year/Semester of Study 1 / Spring Semester
Level of Course 2nd Cycle Degree Programme
Type of Course Compulsory
Department ANTRENöRLüK EğITIMI ANABILIM DALı YüKSEK LISANS (ÖNERILEN)
Pre-requisities and Co-requisites None
Mode of Delivery Face to Face
Teaching Period 14 Weeks
Name of Lecturer ERHAN IŞIKDEMİR (erhanisikdemir@nevsehir.edu.tr)
Name of Lecturer(s)
Language of Instruction Turkish
Work Placement(s) None
Objectives of the Course
It aims to gain the statistical knowledge and skills necessary in the processes of planning, conducting and analyzing the data obtained in the field of sports sciences.

Learning Outcomes PO MME
The students who succeeded in this course:
LO-1 Understanding the philosophy and principles of scientific research techniques and statistics PO-1 Understands scientific research methods and processes and can apply these methods in the field of sports sciences.
Examination
LO-2 Learning scientific research techniques and methods commonly used in sport sciences PO-1 Understands scientific research methods and processes and can apply these methods in the field of sports sciences.
Examination
LO-3 To be able to apply various data collection and analysis methods PO-1 Understands scientific research methods and processes and can apply these methods in the field of sports sciences.
Examination
LO-4 Understanding research ethics and conducting research in accordance with ethical rules PO-1 Understands scientific research methods and processes and can apply these methods in the field of sports sciences.
Examination
LO-5 To be able to perform statistical analysis in computer environment PO-1 Understands scientific research methods and processes and can apply these methods in the field of sports sciences.
Examination
LO-6 To be able to prepare a research proposal and report PO-1 Understands scientific research methods and processes and can apply these methods in the field of sports sciences.
Examination
PO: Programme Outcomes
MME:Method of measurement & Evaluation

Course Contents
This course covers the fundamental stages of the scientific research process, concepts of research population and sample, data collection methods (survey, observation, interview, etc.), data analysis through parametric and non-parametric tests, cause-and-effect relationships, factor and cluster analysis, reliability analysis, and the use of computer-assisted statistical programs such as SPSS and R to enhance and accelerate these processes.
Weekly Course Content
Week Subject Learning Activities and Teaching Methods
1 Introduction to scientific research: Problem definition and hypothesis formation Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
2 Research methods: Population, sample, and data collection techniques Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
3 Statistical concepts: Basic definitions and types of data Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
4 Data organization and descriptive statistics (mean, standard deviation, etc.) Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
5 Parametric tests: t-test and analysis of variance (ANOVA) Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
6 Non-parametric tests: Chi-square test and Mann-Whitney U test Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
7 Introduction to SPSS and basic data analysis Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
8 mid-term exam
9 Regression and correlation analysis: Examining cause-effect relationships Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
10 Factor and cluster analysis: Structuring data Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
11 Reliability analysis: Consistency of measurement tools Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
12 Practical analysis with sample datasets in sports sciences Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
13 Introduction to R software and basic statistical analyses Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
14 Interpretation and reporting of research results Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
15 General review and case studies Lecture and Discussion, Computer Applications, Group Work, Practical Data Analyses, Case Studies and Project Development
16 final exam
Recommend Course Book / Supplementary Book/Reading
1 Erdoğan, S. (2019). Spor Bilimlerinde İstatistiksel Yöntemler ve Uygulamaları. Pegem Akademi Yayıncılık.
2 Gürbüz, H., & Şahin, M. (2018). Spor İstatistiği ve Uygulamaları. Nobel Yayın Dağıtım.
3 Eroğlu, S. (2020). Spor ve Egzersiz Bilimlerinde İstatistiksel Yöntemler. Vize Yayıncılık.
Required Course instruments and materials
SPSS, R, Textbook, PC

Assessment Methods
Type of Assessment Week Hours Weight(%)
mid-term exam 8 1
Other assessment methods
1.Oral Examination
2.Quiz
3.Laboratory exam
4.Presentation
5.Report
6.Workshop
7.Performance Project
8.Term Paper
9.Project
final exam 16 1

Student Work Load
Type of Work Weekly Hours Number of Weeks Work Load
Weekly Course Hours (Theoretical+Practice) 3 14 42
Outside Class
       a) Reading 10 1 10
       b) Search in internet/Library 5 4 20
       c) Performance Project 10 1 10
       d) Prepare a workshop/Presentation/Report 10 1 10
       e) Term paper/Project 0
Oral Examination 0
Quiz 0
Laboratory exam 0
Own study for mid-term exam 10 1 10
mid-term exam 1 1 1
Own study for final exam 10 4 40
final exam 1 1 1
0
0
Total work load; 144