Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Graduate School of Sciences
  • Department of Statistics
  • Master of Science (MS) Degree
  • Course Structure Diagram with Credits
  • Multiple Relation Techniques for Questionnaires Analysis
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title İST517 - Multiple Relation Techniques for Questionnaires Analysis
Course Type Elective Courses
Language of Instruction Türkçe
Laboratory + Practice 3+0
ECTS 7.5
Course Instructor(s) DOÇENT ZERRİN AŞAN GREENACRE
Mode of Delivery The mode of delivery of this course is face to face
Prerequisites There is no prerequisite or co-requisite for this course.
Courses Recomended There is no recomended optional programme component for this course.
Recommended Reading List Dunteman G. H., Ho Ho M. H. R. (2006) An introduction to generalized linear models. Sage publication.
Assessment methods and criteria There will be one midterm, homework and a final exam. The midterm and the final exam will be paper-and-pencil. The students need to carry out a research paper as homework.
Work Placement N/A
Sustainability Development Goals

Content

Weeks Topics
Week - 1 Explain and type of survey data
Week - 2 Explain and analysis categorical data
Week - 3 Create two-multivariate contingency table
Week - 4 Association analysis for contingency table
Week - 5 Correlation coefficients for contingency tables
Week - 6 Define multivariate statistical analysis techniques for categorical data.
Week - 7 Define graphical analysis techniques for categorical data analysis.
Week - 8 Explain multivariate statistical analysis techniques based on modeling for categorical data
Week - 9 Explain Log liner models
Week - 10 Explain correspondence analysis.
Week - 11 Explain logistic regresyon
Week - 12 Explain confirmatory and explanatory factor analysis
Week - 13 Obtaining and preparing survey data for a specific subject where analysis techniques will be applied
Week - 14 Selection and application of the analysis technique suitable for the survey data prepared

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Question & Answer
  • Observation
  • Field Trip
  • Experiment
  • Case Study
  • Brain Storming
  • Report Preparation and/or Presentation
  • Competences
  • True to core values
  • Questoning
  • Entrepreneur
  • Effective use of Turkish
  • Environmental awareness

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%) 0
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