YBS607


Course Title Course Code Program Level
RESEARCH DESIGN, DATA COLLECTION AND ANALYSIS YBS607 Management Information Systems (Doctorate) M.A / M.Sc.

Course Term
(Course Semester)
Teaching and Learning Methods
Credits
Theory Practice Lab Projects/Field Work Seminars/Workshops Other Total Credits ECTS Credits
02
(Spring)
42 28 36 80 186 3 10

Teaching Staff Dr. Öğr. Üyesi MESUT ÜNLÜ
Language of Instruction Türkçe (Turkish)
Type Of Course Compulsory
Prerequisites
Recommended Optional Programme Component
Course Objectives At the end of this course, students are expected to master the concepts of the entire research process, including the design of a scientific research, data analysis, and writing a research report.
Course Content This course covers the basic components and theoretical framework of scientific research and research design elements, various qualitative and quantitative data collection tools and methods, data analysis and relational and group difference tests and hypothesis testing, etc.
Learning Outcomes (LO) Students who complete and succeed this course will acquire those skills as follows; 1. They will comprehend the elements of research design. 2. They will apply various qualitative and quantitative data collection tools and methods. 3. They will apply hypothesis testing with data analysis and relational and group difference tests. 4. They will have the skills of interpretation and presentation of findings.
Mode of Delivery Face to face
Course Outline
Week Topics
1. Week Philosophy and Structure of Research
2. Week Components of the Research Study
3. Week Induction and Deduction
4. Week Scientific Research Approaches
5. Week Determining the Research Problem
6. Week Establishing the Theoretical Framework
7. Week Variable and scale in research
8. Week Midterm
9. Week Hypothesis and Hypothesis Tests
10. Week Descriptive Statistics Tests
11. Week Parametric Tests
12. Week Non-Parametric Tests
13. Week Reliability and Validity in Measurement
14. Week Writing Research Proposal
Assessment
  Percentage(%)
Mid-term (%) 40
Quizes (%)
Homeworks/Term papers (%)
Practice (%)
Labs (%)
Projects/Field Work (%)
Seminars/Workshops (%)
Final (%) 60
Other (%)
Total(%) 100
Course Book (s) and/or References 1. Tabachnick, B. G, & Fidel, L. S. (2001). Using Multivariate Statistics (Fourth edition). Boston: Ally and Bacon 2. Büyüköztürk, Ş. (2007). Veri Analizi El Kitabı, Ankara: Pegem
Work Placement(s)
The Relationship between Program Qualifications (PQ) and Course Learning Outcomes (LO)