Research and Statistics In Sports Sciences
Movement and Training (Master) (With Thesis)
Institute of Health Sciences
Second Cycle (Master's Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Research and Statistics In Sports Sciences | HAB501 | Compulsory | Master's degree | 1 | Fall | 7 |
Name of Lecturer(s)
Associate Prof. Dr. Hakan AKDENİZ
Learning Outcomes of the Course Unit
1) Explain the types of Scientific Research
2) Explain the variables and their types.
3) Explain the basic concepts related to statistics.
4) Explain the importance of statistics for sports sciences.
5) Makes tables, figures and graphics.
6) Introduces hypothesis testing and assumptions
7) Introduce the parametric hypothesis tests.
8) Introduce nonparametric hypothesis tests.
9) Introduces regression and correlation.
10) Introduces Survival Analysis
Program Competencies-Learning Outcomes Relation
| Program Competencies | |||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | ||
| Learning Outcomes | |||||||||||||
| 1 | Middle | No relation | No relation | No relation | No relation | Middle | No relation | No relation | No relation | High | No relation | No relation | |
| 2 | Middle | No relation | No relation | No relation | Low | No relation | No relation | No relation | No relation | No relation | Low | No relation | |
| 3 | No relation | No relation | No relation | Low | No relation | No relation | No relation | No relation | No relation | Middle | No relation | No relation | |
| 4 | Middle | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | Low | |
| 5 | No relation | No relation | No relation | No relation | High | No relation | No relation | No relation | High | No relation | No relation | No relation | |
| 6 | No relation | No relation | No relation | No relation | Middle | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 7 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 8 | No relation | No relation | No relation | Low | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 9 | No relation | No relation | No relation | High | No relation | No relation | No relation | No relation | No relation | No relation | Middle | No relation | |
| 10 | No relation | No relation | No relation | High | High | High | No relation | No relation | No relation | No relation | Middle | No relation | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Not Required
Course Contents
The research includes definitions and types, planning, research subject selection, scanning resources, determining research goals, determining the research society and sample, determining data summarization techniques, Basic Statistical Terms, Parametric and Non-Parametric Hypothesis Tests, Regression and Correlation Analysis, Survival Analysis.
Weekly Schedule
1) Research definition and types, planning, Selection of research subject, Searching resources, Determining research objectives2) Determination of research society and sample, determination of data summarization techniques, Tabulation and Graphics
3) Basic Statistics Terms, Definitions, Symbol Representations, Data Collection in Sports Science, Classification of Data According to Variable Type, Processing
4) Frequency and Theoretical Distributions, Sampling Methods, Descriptive Statistics for Classified and Unclassified Data (such as Average S.Dev) Calculation in SPSS, Graphic Representation of Data
5) Definition of Hypothesis Tests, their assumptions, Purposes, Errors and Significance Levels
6) Definition of Parametric Tests, Assumptions, T Test Application Conditions, Single Sample T Test Model, Two Sample T Test Models and Sample Applications and Comments in SPSS
7) Dependent Sample T Test Models and Sample Applications and Comments in SPSS
8) Midterm
9) Variance Analysis Definition, assumptions, One-Way Analysis of Variance, Two-Way Analysis of Variance, Repeated Measures Variance Analysis and Sample Applications and Comments in SPSS
10) Definition of Nonparametric Tests, their assumptions, Mann-Whitney U Test, Wilcoxon T Test Application Conditions, Models and Sample Applications and Comments in SPSS
11) Nonparametric Analysis of Variance Definition, assumptions, Kruskal Wallis Analysis, Friedman Analysis and Sample Applications and Comments in SPSS
12) Kikare Test assumptions and application conditions, Pearson chi-square test and Yates Chi-square Test, Sample Applications and Comments in SPSS
13) Fisher exact chi-square test and Mc Nemar chi-square test, Sample Applications and Comments in SPSS
14) Regression and Correlation Analysis Definition, assumptions, Linear Regression Analysis, Logistic Regression Analysis, Correlation Analysis, and Sample Applications and Comments in SPSS
15) Life Analysis Definition, assumptions, Kaplan Meier Life Analysis, Cox Regression Analysis and Sample Applications and Comments in SPSS
16) Final Exam
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
1) Lecture
2) Lecture
3) Question-Answer
4) Question-Answer
5) Group Study
6) Group Study
7) Problem Solving
Assessment Methods and Criteria
Contribution of Midterm Examination to Course Grade |
30% |
|---|---|
Contribution of Final Examination to Course Grade |
70% |
Total |
100% |
Language of Instruction
Turkish
Work Placement(s)
Not Required