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TR

DATA ANALYSIS AND COMPUTER APPLICATIONS IN BUSINESS

Course
BUSN631 - DATA ANALYSIS AND COMPUTER APPLICATIONS IN BUSINESS
Department
Business Administration - English - PhD
Course Type
Course
Status
Required
Language
English
Credit
3
ECTS
8
T+P+L
3 + 0 + 0
Course Coordinator(s)
-
Prerequisite
-
Keywords

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 AND COMPUTER APPLICATIONS IN BUSINESS

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

No course outcomes have been defined yet.

Course Syllabus

Week Topic
Week 1 Introduction of the course, overview / Basics of data analysis
Week 2 How to design a quantitative research
Week 3 Introduction to SPSS
Week 4 Descriptives, cross-tables, frequencies
Week 5 Reliability and validity
Week 6 Reliability and validity (Class Practice)
Week 7 T-test, ANOVA
Week 8 Midterm
Week 9 Correlation
Week 10 Correlation (Class Practice)
Week 11 Regression
Week 12 Regression (Class Practice)
Week 13 Structural Equation Modelling
Week 14 Mediation-Moderation
Week 15 Mediation-Moderation (Class Practice)

Reference Books & Course Materials

  1. 01 Field, A. 2024 . Discovering Statistics Using IBM SPSS Statistics, 6th ed., Sage, London.
  2. 02 Pituch, K.A. & Stevens, J.P. 2016. Applied multivariate statistics for the social sciences, Taylor& Francis: New York.
  3. 03 Te Grotenhuis, M. & Matthijssen, A. 2016. Basic SPSS Tutorial, Sage: UK.

Learning Outcomes

  1. L01 Listing basic analysis techniques SOLO 3
  2. L02 Formulate research problems SOLO 4
  3. L03 Creates quantitative models SOLO 5
  4. L04 Evaluate approperiate statistical methods SOLO 5
  5. L05 Formulates research hypotheses SOLO 4

Program Outcomes

  1. P01 PO1 Become competent in searching and comprehending the relevant academic articles, interpreting the information learnt or obtained via various channels and absorbing exceptional knowledge in their field.
  2. P02 PO2 Devoted themselves to be a qualified researcher and knowledge worker in their field all throughout their life and career.
  3. P03 PO3 Demonstrated that they developed their individual capabilities through written projects, assignments and presentations that they will independently implement both in academia and work contexts.
  4. P04 PO4 Gained key practical skills and knowledge which need to be implemented in their own research and business work environment.
  5. P05 PO5 Been able to implement critical and analytical thinking and analyses into their studies, research and work.
  6. P06 PO6 Become proficient in adopting the gained knowledge into practice and research in a critical, and analytical way.
  7. P07 PO7 Become experts in using information technology tools for their studies, research and workplace in an ethical and safely environment by sharing and transferring their knowledge.
  8. P08 PO8 Succeeded in working, researching and forming partnerships with their colleagues/team members in a global environment.
  9. P09 PO9 Proved themselves capable of disseminating and sharing knowledge, sustainingly communicating with others, in any global workplace or research setting.
  10. P10 PO10 Become capable of interpreting and transferring their qualified knowledge into practice and research.
  11. P11 PO11 Dedicated themselves to applying advanced academic studies and enrolled themselves in work or non-work projects related to environmental approaches and ethical issues.

Po-Lo Matrix

LO P01 P02 P03 P04 P05 P06 P07 P08 P09 P10 P11 Average
L01 4 5 4 4 5 4 5 3 3 4 3 4
L02 4 5 4 4 4 5 4 4 5 4 3 4.18
L03 5 4 4 5 4 4 5 4 5 3 3 4.18
L04 5 4 4 5 4 4 4 5 4 4 4 4.27
L05 4 4 5 4 4 4 4 5 4 4 3 4.09