Educational Statistics II
Measurement and Evaluation in Education
Institute of Social Sciences
Second Cycle (Master's Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Educational Statistics II | EGD109 | Compulsory | Master's degree | 1 | Spring | 7 |
Name of Lecturer(s)
Associate Prof. Dr. Fatih KEZER
Learning Outcomes of the Course Unit
1) S/he can define the basic concepts of advanced statistics.
2) S/he can tell the assumptions of multivariate statistical techniques.
3) S/he can check whether the data meet the assumptions of multivariate statistical techniques.
4) S/he can perform regression analysis with discontinuous data.
5) S/he can interpret the significance level of multivariate difference analysis.
6) S/he can do exploratory factor analysis.
7) S/he can do comfirmatory factor analysis.
8) S/he can do classification analysis of data and individuals.
9) S/he can examine and interprets the relationship and explanation levels between artificial neural networks, decision trees and data mining methods.
10) S/he can report the results obtained.
Program Competencies-Learning Outcomes Relation
| Program Competencies | |||||||||||||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | ||
| Learning Outcomes | |||||||||||||||||||||||
| 1 | Low | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 2 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 3 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 4 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 5 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 6 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 7 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 8 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 9 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 10 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
.
Course Contents
Ancova. Manova. Mancova Logistic regression. Hierarchical regression. Multivariate regression. Exploratory factor analysis. Confirmatory factor analysis. Discriminant analysis. Cluster analysis. Artificial neural networks. Decision trees. Data mining.
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
1) Lecture
2) Lecture
3) Question-Answer
4) Question-Answer
5) Discussion
6) Discussion
7) Group Study
8) Group Study
9) Self Study
10) Self Study
11) Project Based Learning
12) Project Based Learning
Assessment Methods and Criteria
Contribution of Midterm Examination to Course Grade |
40% |
|---|---|
Contribution of Final Examination to Course Grade |
60% |
Total |
100% |
Language of Instruction
Turkish
Work Placement(s)
Not Required