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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 Computer Education and Instructional Technology
  3. PhD in Computer Education and Instructional Technology
  4. PhD in Computer Education and Instructional Technology
  5. Course Structure Diagram with Credits
  6. Statistical Methods in Instructional Technology
  7. Description
  • Description
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Last Updated: 30/09/2026

Code - Course Title Course Type Laboratory + Practice ECTS
İST634 - Statistical Methods in Instructional Technology II. SEMESTER 3 +0 7.5
Language of Instruction Türkçe
Course Type Elective Courses
Course Instructor(s) PROF. DR. ADİLE AŞKIM KURT
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 not applicable
Recommended Resources
Work Placement N/A
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Introduction to the program and setting rules for the lesson Basic concepts.
Week - 2 Data entry and creating tables.
Week - 3 Descriptive statistics (mean, standard deviation, mod, median)
Week - 4 t test (one sample, dependent, independent)
Week - 5 Variance analysis (ANOVA / one way, two way)
Week - 6 Variance analysis (ANOVA / one way, two way)
Week - 7 Multiple analysis of variance (MANOVA)
Week - 8 Factorial designs
Week - 9 Multiple comparing tests (post hoc)
Week - 10 Analysis of covariance (ANCOVA, MANCOVA)
Week - 11 Chi-Square Analysis
Week - 12 Analysis of correlation
Week - 13 Analysis of regression
Week - 14 general assesment

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

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