Course Information

Course Title	Code	Semester	L+U Hour	Credits	ECTS
CATEGORICAL DATA ANALYSIS	803400815031		3 + 0	3.0	10.0

Prerequisites

None

Language of Instruction	English
Course Level	Graduate Degree
Course Type	Elective
Mode of delivery
Course Coordinator
Instructors
Assistants
Goals	To give theoretical and practical knowledge about the appropriate analysis and visualization techniques; and make the students competent to make research and analysis on the topic.
Course Content	Definition of Categorical Variable, Measurement Scales, Probability Distribution Functions Used in Analysis of Categorical Data, Contingency Tables, Advanced Methods in Contingency Analysis
Learning Outcomes	1) Gains knowledge regarding the categorical data and their taxonomy. 2) Learns the analysis methods applicable for categorical data analysis. 3) Gains knowledge regarding the probability distribution functions; and their applicability in daliy life problems.

Week	Topics	Teaching and Learning Methods and Techniques	Study Materials
1. Week	Introduction to Data and Related Terms/Definitions	Lecture	Homework
2. Week	Classification of Data; Taxonomy of Categorical Data	Lecture	Homework
3. Week	Fundamentals of Probability	Lecture	Homework
4. Week	Fundamentals of Probability	Lecture	Homework
5. Week	Probability Distribution and Density Functions	Lecture	Homework
6. Week	Independence Tests	Lecture	Homework
7. Week	Statistical Significance	Lecture	Homework
8. Week	Çok Boyutlu Ölçeklendirme Analizi	Lecture	Homework
9. Week	Principle Component Analysis	Lecture	Homework
10. Week	Kategorik Veri Görselleştirme Teknikleri	Lecture	Homework
11. Week	Categorical Data Visualization Techniques	Lecture	Homework
12. Week	Studies on Daily Life Problems	Lecture	Homework
13. Week	Studies on Daily Life Problems	Lecture	Homework
14. Week	Studies on Daily Life Problems	Lecture	Homework

Recommended Sources

ANDERSEN, B. Earling, The statistical analysis of Categorical Data, Springer Verlag, Third edition, Berlin, 1994.

GREENACRE, J. Michael, Correspondence Analysis In Practice, Academic Press, Harcourt Brace & Company Publishers, London, 1993.

*DK = Course's Contrubution.

	0	1	2	3	4	5
Level of contribution	None	Very Low	Low	Fair	High	Very High

Event	Quantity	Duration (Hour)	Total Workload (Hour)
Course Duration (Total weeks*Hours per week)	14	3	42
Work Hour outside Classroom (Preparation, strengthening)	14	9	126
Homework	2	20	40
Presentation (Including Preparation Time)	1	20	20
Seminar	1	1	1
Midterm Exam	1	1	1
Time to prepare for Midterm Exam	1	20	20
Final Exam	1	1	1
Time to prepare for Final Exam	1	40	40
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course			30