Course Language:
English
Course Objectives:
The course objective is to explain the importance of scientific investigation and to illustrate the application of advanced quantitative research techniques. The course is mainly intended to teach empirical approach, measurement process, and the use of statistical techniques for data analysis purposes. |
Course Content:
The course includes in the data analyzing methods; such as parametric and nonparametric methods, factorial experiment with repeated and nonrepeated measures (ANOVA analysis), correlation and regression analysis, exploratory factor analysis and confirmatory factor analysis, and structural equation modelling. For purpose of data analysis, it is used SPSS, PROCESS and AMOS statistical programs and SmartPLS (if it’s available). Therefore, students will learn to use the SPSS, PROCESS and AMOS programs. |
Teaching Methods:
1. Lecture 2. Question/Answer 3. Discussion Method 4. Case Study 5. Workshop 6. Problem Solving Method
Assessment Methods:
A: Exam , B: Homework, C: Presentations, D: Project
Vertical Tabs
Course Learning Outcomes
Learning Outcomes | Program Learning Outcomes | Teaching Methods | Assessment Methods |
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1,2,3,4 | 1,2,3,4 | A, B, D |
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1,2,3,4 | 1,2,3,4 | A, B, D |
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1,2,3,4 | 1,2,3,4 | A, B, D |
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1,2,3,4 | 1,2,3,4 | A, B, D |
Course Flow
COURSE CONTENT | ||
Week | Topics | Study Materials |
1 | Understanding the research process, measurement, collecting data and questionnaire design. |
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2 | Sampling procedures. |
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3 | Understanding formal statistical tests. |
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4 | Parametric and nonparametric tests with SPSS. |
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Exercises /cases |
5 |
Variance analysis with SPSS (ANOVA, ANCOVA and MANCOVA analyses).
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Exercises /cases |
6 | Measuring statistical association with SPSS (Correlation analysis and regression analysis). |
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Exercises /cases |
7 | Testing mediation with regression analysis using SPSS and PROCESS. |
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Exercises /cases |
8 | Midterm exam | -- |
9 |
Testing moderation with regression analysis using SPSS and PROCESS.
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Exercises /cases |
10 |
Structural Equation Modeling with AMOS (Confirmatory factor analysis)
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Exercises /cases |
11 |
Structural Equation Modeling with AMOS (Path analysis)
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Exercises /cases |
12 |
Specific Indirect Effect Analysis with User-define Estimands in AMOS.
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13 |
Multi-group analysis with AMOS and SmartPLS.
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14 |
Impotance-Performance analysis with SmartPLS.
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Exercises /cases |
15 |
Cluster analysis with SmartPLS.
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Exercises /cases |
16 | Final Exam | -- |
Recommended Sources
RECOMMENDED SOURCES | |
Textbook |
-SPSS for Windows Made Simple, Kinnear and Gray, Hillsdale (USA).
-A primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), Hair, Hult, Ringle, Sarstedt (2017), Thousand Oaks, Sage. -Notes and cases developed by instructor -Marketing Research, Kinnear and Taylor, McGraw Hill.
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Additional Resources |
Saunders, M., Lewis, P. & Thornhill, A. (2012) Research Methods for Business Students, (6th.ed.), Pearson.
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Material Sharing
MATERIAL SHARING | |
Documents | Power point presentation related to all concepts discussed in the class. |
Assignments | A research project |
Exams | One midterm exam, one final exam |
Assessment
ASSESSMENT | ||
IN-TERM STUDIES | NUMBER | PERCENTAGE |
Mid-term | 1 | 40 |
Final | 1 | 60 |
Total | 100 |
Course’s Contribution to Program
COURSE'S CONTRIBUTION TO PROGRAM | ||||||
No | Program Learning Outcomes | Contribution | ||||
1 | 2 | 3 | 4 | 5 | ||
1 | Ph.D. candidates gain knowledge and skills to interpret and criticize many theories, models, and paradigms related to different perspectives that developed in the fields of business (organization and administration, organization behavior, marketing, finance, human resources, production technology, etc.) and social sciences and evaluation of scientific studies and research presented at scientific meetings | X | ||||
2 | Ph.D. candidates learn to track and interpret the changes, innovations and developments in business administration or in other fields of social sciences, and as practitioners determine the organizational and managerial problems, create innovative solutions in the light of this information. | X | ||||
3 | Ph.D. candidates gain knowledge, ability, and responsibility to carry out unique scientific and academic researches independently or in partnership with other researchers in the field of social sciences, and to publish the research results in forms of book, article, report and to present for discussing in scientific areas. | X | ||||
4 | Ph.D. candidates become managers based on ethical issues, leaders, or academicians who have consciousness of a sustainable environment, social responsibility and active citizenship in the scientific environment in the university, in the close relationship with outstanding faculty members, selected guest speakers and the teammates who they are educated together. | X | ||||
5 | Ph.D. candidates learn that the employees of the national and international organizations they manage come from different backgrounds and culture, cultural conflicts occur in mergers and cross-country mobility of the labor force, in a scientific environment and evolve as successful managers and leaders who can manage cultural differences. | X | ||||
6 | Ph.D. candidates gain leadership qualifications to make rational decision-making for long-term strategic planning and application of plans in the organizations they work. | X | ||||
7 | Ph.D. candidates learn that strategic management is teamwork and results can be achieved only by working as teams. | X | ||||
8 | Ph.D. candidates learn that information developed in different fields of social sciences complete each other and in scientific studies, having multidisciplinary approach and viewpoint is inevitable. | X | ||||
9 | In long-term doctoral studies, Ph.D. candidates prepare papers and presentations in English and they criticized for improvement of their studies, they gain effective communication skills in both their native language and in English. | X | ||||
10 | Ph.D. Candidates experiences how rapid is production and development of information in social sciences and in business administration and learn that life-long learning is inevitable. | X |
ECTS
ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION |
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Activities | Quantity |
Duration (Hour) |
Total Workload (Hour) |
Course Duration (Including the exam week: 16x Total course hours) | 16 | 3 | 48 |
Hours for off-the-classroom study (Pre-study, practice) | 16 | 5 | 80 |
Mid-terms | 1 | 4 | 4 |
Assignment | 16 | 8 | 128 |
Final examination | 1 | 4 | 4 |
Total Work Load | 264 | ||
Total Work Load / 25 (h) | 10,56 | ||
ECTS Credit of the Course | 10 |