DATA ANALYSIS & COMPUTER APPLICATIONS IN MANAGEMENT
- Course
- BUSN531 - DATA ANALYSIS & COMPUTER APPLICATIONS IN MANAGEMENT
- Department
- Master of Business Administration - English - Master
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 8
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- Prof. Dr. Cem TANOVA
- Prerequisite
- -
Course Description
This course covers a description of the research process in general and each of the steps involved in more detail. The course focuses on alternative ways of carrying out each step and guidelines for selecting among these alternatives according to the needs of a specific research problem. The course also describes using software packages like SPSS and interpretation of the results of data analysis. Course is designed to enable student to apply commonly used statistical techniques to different datasets. For this purpose, the course will focus on descriptive analysis, correlation, t-test, ANOVA, regression and mediation and moderation analysis. The students will use SPSS software to work on the datasets.
DATA ANALYSIS & COMPUTER APPLICATIONS IN MANAGEMENT
Evaluation Tools (Active Term)
| Item | Type | Weight (%) |
|---|---|---|
| Midterm | Midterm | 40 |
| Final | Final | 45 |
| Project | Project | 15 |
| Total | 100 | |
Course outcomes
No course outcomes have been defined yet.
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | Introduction of the course, overview / Research process |
| Week 2 | Descriptive statistics |
| Week 3 | Introduction to SPSS/Data cleaning |
| Week 4 | Descriptive statistics (Class Practice) |
| Week 5 | Reliability and validity |
| Week 6 | Reliability and validity (Class Practice) |
| Week 7 | Reliability and validity (Class Practice) |
| Week 8 | Midterm |
| Week 9 | T-test, ANOVA |
| Week 10 | T-test, ANOVA (Class Practice) |
| Week 11 | Correlation |
| Week 12 | Correlation (Class Practice) |
| Week 13 | Regression |
| Week 14 | Regression (Class Practice) |
| Week 15 | Data Practice |
Reference Books & Course Materials
- 01 Field, A. 2024. Discovering Statistics Using IBM SPSS Statistics, Sage, London.
- 02 Pituch, K.A. & Stevens, J.P. 2016. Applied multivariate statistics for the social sciences, Taylor& Francis: New York.
- 03 Te Grotenhuis, M. & Matthijssen, A. 2016. Basic SPSS Tutorial, Sage: UK.
Learning Outcomes
No learning outcomes have been defined.
Program Outcomes
- Demonstrate advanced knowledge of core concepts and theoretical frameworks in Management Information Systems, and apply them to develop innovative models that reflect current advancements in the field.
- Analyze complex organizational problems and design integrated information systems solutions by applying advanced MIS knowledge and synthesizing multiple theoretical perspectives.
- Develop and manage database systems and data-driven applications that ensure effective storage, retrieval, and use of organizational data in real-world contexts.
- Utilize data analytics, business intelligence tools, and data visualization techniques to extract actionable insights and support strategic, data-driven decision-making.
- Evaluate and apply emerging technologies such as AI, IoT, and Blockchain to drive digital transformation, enhance organizational performance, and formulate original research inquiries.
- Conduct independent and collaborative research using appropriate methodologies, and communicate findings effectively through scholarly writing and presentations suited to diverse audiences.
- dentify and address ethical, legal, and societal implications in the research, development, and use of information technologies, adhering to scientific and professional standards.
- Collaborate effectively in multidisciplinary teams and demonstrate leadership in addressing complex technology-driven challenges.
- Apply project management methodologies and tools to plan, execute, and monitor IT projects within organizational settings.
- Develop and integrate information systems that align with organizational goals and strategies, supporting innovation and sustainable growth.
- Perform comprehensive systems analysis and design, including requirements gathering, modeling, prototyping, and evaluating enterprise system architectures such as ERP, CRM, and SCM.
- Assess and mitigate organizational information security risks by applying appropriate principles, technologies, and best practices in cybersecurity.
Po-Lo Matrix
The PO-LO matrix has not been populated yet.