OLC630 - DATA ANALYSES METHODS IN EDUCATIONAL RESEARCH

Course Name Code Semester Theory
(hours/week)		 Application
(hours/week)		 Credit ECTS
DATA ANALYSES METHODS IN EDUCATIONAL RESEARCH OLC630 Any Semester/Year 2 2 3 8
PrequisitesEOD 645
Course languageTurkish
Course typeElective 
Mode of DeliveryFace-to-Face 
Learning and teaching strategiesLecture
Discussion
Question and Answer
Problem Solving
Other: aplication  
Instructor (s)Prof. Dr. Selahattin GELBAL 
Course objectiveTo know and understand the statistical hypothesis tests used in educational research and to apply these tests appropriately. 
Learning outcomes
  1. To explain assumptions of statistical tests and their applications.
  2. To apply statistical analyses that may be necessesary for the solution of a new research problem.
  3. To interpret and report statistical test results according to the problem.
Course ContentHypothesis tests and their applications, one ? factor and multiple ? factor analysis of variance methods, non-parametric tests, one ? factor and multiple ? factor analysis of covariance methods, analysis of variance with within - subject designs, analysis of variance with planned and post hoc comparisons, simple regression analysis, multivariate regression analysis, logistic regression analysis, exploratory and confirmatory factor analyses 
ReferencesBaykul, Y. (1999), İstatistik metodlar ve uygulamalar (3. baskı). ANKARA: Anı Yayıncılık.
Gravetter, F. J. & Wallnau, L. B. (1992). Statistics for the behavioral sciences: A first course for students (3rd ed.). St. Paul: West Publishing Company.
Hicks, C. R. (çev. Z. Muluk, Ö. Toktamış, S. Kurt & E. Karaağaoğlu) (1985). Deney düzenlemede istatistiksel yöntemler. Ankara: Akademi Matbaası.
Freund, J. E. & Simon, G. A. (1992). Modern elementary statistics (8th ed.). New Jersey: Prentice Hall.

 

Course outline weekly

WeeksTopics
Week 1Overview of hypothesis testing and its relationship to ANOVA
Week 2F Distribution and its properties and one-way ANOVA
Week 3ANOVA and ANCOVA in one-factor variables
Week 4Variance analysis methods in multi-factor variables
Week 5Co-variance analysis methods in multi-factor variables
Week 6One-factor analysis of variance in repeated data
Week 7Multi-factor analysis of variance in repeated data
Week 8Midterm
Week 9Simple linear regression
Week 10Introduction to multivariate regression analysis
Week 11Multivariate regression analysis application
Week 12Exploratory factor analysis
Week 13Confirmatory factor analysis
Week 14Confirmatory factor analysis
Week 15Preparation to exam
Week 16Final exam

Assesment methods

Course activitiesNumberPercentage
Attendance100
Laboratory140
Application20
Field activities20
Specific practical training00
Assignments70
Presentation00
Project170
Seminar00
Midterms00
Final exam130
Total100
Percentage of semester activities contributing grade succes170
Percentage of final exam contributing grade succes130
Total100

WORKLOAD AND ECTS CALCULATION

Activities Number Duration (hour) Total Work Load
Course Duration (x14) 14 3 42
Laboratory 14 3 42
Application236
Specific practical training000
Field activities236
Study Hours Out of Class (Preliminary work, reinforcement, ect)14342
Presentation / Seminar Preparation000
Project12424
Homework assignment7642
Midterms (Study duration)000
Final Exam (Study duration) 12424
Total Workload5569228

Matrix Of The Course Learning Outcomes Versus Program Outcomes

D.9. Key Learning OutcomesContrubition level*
12345

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest