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About the Programme Academic Staff Program Qualifications Lessons Matrix of Course & Program Qualifications Turkish Qualifications Framework (TQF) TQF & Program Qualifications
  1. Graduate School
  2. Department of Business Administration
  3. PhD in Business Administration
  4. PhD in Quantitative Methods
  5. Course Structure Diagram with Credits
  6. Data Analysis
  7. Description
  • Description
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  • ECTS Credit Load
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Last Updated: 30/09/2026

Code - Course Title Course Type Laboratory + Practice ECTS
SAY613 - Data Analysis I. SEMESTER 3 +0 7.5
Language of Instruction Türkçe
Course Type Elective Courses
Course Instructor(s) PROF. DR. ALİ ÖZDEMİR
Mode of Delivery The mode of delivery of this course is Face to face
Place of Delivery
Used Educational Platforms
Prerequisites There is no prerequisite or co-requisite for this course.
Courses Recomended There is no recommended optional programme component for this course.
Recommended Resources Mining,2007, John Wiley & Sons, New JerseyField, A., 2009, Discovering Statistics Using SPSS, 3 rd edition, Sage.
Work Placement Internship is not suitable for this course.
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Basic language of statistics
Week - 2 Conversion of data to information
Week - 3 Data pre-processing
Week - 4 Data pre-processing
Week - 5 Tables and graphs
Week - 6 Tables and Graphs
Week - 7 Presentation
Week - 8 Descriptive Statistics
Week - 9 Inferential statistics
Week - 10 Inferential statistics
Week - 11 Grouping methods
Week - 12 Grouping Methods
Week - 13 Predictive Modelling
Week - 14 Presentation

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%)

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