GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
CLUSTER ANALYSİS/5121303
Course Title: CLUSTER ANALYSİS
Credits 3 ECTS 7.5
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
To learn the classes of states which make easier some calculations
To be able to calculate the R matrix which gives the mean passage frequencies and the F matrix which gives the ever reaching probabilities among state
To learn the branching processes which is a specific application of Markov chains
To learn the potantiels and excessive functions which are modern tools for the examination of theory of Markov chains and to know the optimal stopping
To learn the related concepts of Markov processes, i.e. continuous parameter Markov chains, parallel to that of discrete parameter Markov chains
To learn the concepts related to renewal, regenerative and Markov renewal processes
 -- MODE OF DELIVERY
  The mode of delivery of this course is face to face.
 --WEEKLY SCHEDULE
1. Week  Markov chains, visits to a fixed state, classification of states
2. Week  Computation of R and F matrices
3. Week  Recurrent states and the limiting probabilities, transient and periodic states
4. Week  Branching processes
5. Week  Potantiels and excessive functions, optimal stopping
6. Week  Games with discounting and fees
7. Week  Markov processes, sample path behaviour, structure of a Markov process
8. Week  Midterm Potantiels and generators, limit theorems
9. Week  Renewal processes
10. Week  Regenerative processes and renewal theory
11. Week  Regenerative processes and renewal theory
12. Week  Markov renewal processes
13. Week  Markov renewal functions and classification of states
14. Week  Markov renewal functions and classification of states (continuation)
15. Week  Final examination
16. Week  
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
40
 Assignment
1
10
 Application
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
40
 Percentage of Final Exam to Total Score  
60
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
0
 Reading Tasks
10
7
70
 Searching in Internet and Library
5
3
15
 Material Design and Implementation
0
 Report Preparing
5
2
10
 Preparing a Presentation
0
 Presentation
0
 Midterm Exam and Preperation for Midterm Exam
3
6
18
 Final Exam and Preperation for Final Exam
3
10
30
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
185
 TOTAL WORKLOAD / 25: 
7.4
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
11. Based on the capabilities of undergraduate level, the students enrolled to the program can develop and deepen their knowledge and skill at the level of expertise on the same field of the undergradute study or a different field.X
22. The students use their theoretical and practical knowledge at the level of expertise in the area of statistics.X
33. The students should evaluate their acquired knowledge and skills in a critical perspective and the critical point of view guides their learning process.X
44. Theoretical and practical knowledge gained in graduate level in the field of Statistics should be applied and transfer to the current problems.X
55. By performing the process from the identification of the scientific research problem to reporting and the process should be transferred in oral, written and visual ways.X
66. The students should use computer software and information technologies on the level required by the field of Statistics.X
77. The students should have the ability to use Statistics in interdisciplinary studies.X
88. The students should have enough foreign language level to pursue statistical literature.X
99. At the required level of field of statistics, he/she should use statistical software and information technology efficiently in a such a way that helps solving problems in his/her research.X
1010. In the process of applying knowledge in a professional sense, social, scientific, and ethical values should be regarded.X
 -- NAME OF LECTURER(S)
   (Prof. Dr. Yaprak Arzu ÖZDEMİR)
 -- WEB SITE(S) OF LECTURER(S)
   (http://www.websitem.gazi.edu.tr/site/yaprak)
 -- EMAIL(S) OF LECTURER(S)
   (yaprak@gazi.edu.tr)