Course Information

Course Information
Course Title Code Language Type Semester L+U Hour Credits ECTS
- SYP503 Turkish Compulsory 3 + 0 3.0 9.0
Prerequisite Courses
Course Level Graduate
Mode of delivery Face to face
Course Coordinator
Instructor(s) Doç. Dr. Reşat SADIK (Bahar), Doç. Dr. Reşat SADIK (Güz)
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
# Öğrenme Kazanımı
1 Recognizes the data that can be obtained in researches in terms of their characteristics,
2 Creates an appropriate data collection tool in a case under study.
3 Prepares the available data for analysis with appropriate methods in a case under investigation.
Lesson Plan (Weekly Topics)
Week Topics/Applications Method
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
*Midterm and final exam dates are not specified in the 14-week course operation plan. Midterm and final exam dates are held on the dates specified in the academic calendar with the decision of the University Senate.
Relations with Education Attainment Program Course Competencies
Program Requirements DK1 DK2 DK3
ECTS credits and course workload
ECTS credits and course workload Quantity Duration (Hour) Total Workload (Hour)
Sınavlar
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
*AKTS = (Total Workload) / 25,5 ECTS Credit of the Course 9.0