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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 Turkish and Social Sciences Education
  3. PhD in Social Studies Education
  4. Course Structure Diagram with Credits
  5. Quantitative Data Analysis
  6. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
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Last Updated: 02/10/2026

Code - Course Title Course Type Laboratory + Practice ECTS
ARY621 - Quantitative Data Analysis I. SEMESTER 3 +0 7.5
Language of Instruction Türkçe
Course Type Elective Courses
Course Instructor(s) PROF. DR. SERVET ÜZTEMUR
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 1. Math 2. Research Methods.
Recommended Resources
Work Placement N/A
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Introduction: The meaning and role of statistics, variable; sales of measurement,population and sample
Week - 2 Organizing and Graphing Data
Week - 3 Describing distirbutions: Individual Scores, Central Tendency, and Variation
Week - 4 The Normal Distribution
Week - 5 Probabilitiy, Sampling Distirbutions, and Sampling Procedures
Week - 6 Hypothesis Testing: One-Sample Case for the Mean
Week - 7 Estimation: One-Sample Case for the Mean
Week - 8 Hypothesis Testing: One-Sample Case for other statistics
Week - 9 Hypothesis Testing: Two-Sample Case for the Mean
Week - 10 Hypothesis Testing: Two-Sample Case for other Statistics
Week - 11 Hypothesis Testing,K-saple case analysis of variance, one-way classification
Week - 12 Analysis of variance, Two- vay classification, Analysis of Covariance
Week - 13 Chi Square test for frequencies
Week - 14 Multiple Linear regression

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
1.Midterm Exam 1 40
Final Exam 1 60
Toplam (%) 100

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