GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
ROBUST STATISTICAL INFERENCE/5141303
Course Title: ROBUST STATISTICAL INFERENCE
Credits 3 ECTS 7.5
Semester 1 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- NAME OF LECTURER(S)
  Asist. Prof. Dr. Necla GÜNDÜZ
 -- WEB SITE(S) OF LECTURER(S)
  www.gazi.edu.tr~ngunduz
 -- EMAIL(S) OF LECTURER(S)
  ngunduz@gazi.edu.tr
 -- LEARNING OUTCOMES OF THE COURSE UNIT
To be aware of the need of robust estimators and to gain the ability of using robust estimators.
 -- MODE OF DELIVERY
   The mode of delivery of this course is Face to face
 -- PREREQUISITES AND CO-REQUISITES
  There is no prerequisite or co-requisite for this course.
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
  There is no recommended optional programme component for this course.
 --COURSE CONTENT
1. Week  A robust approaches to statistical concepts
2. Week  Investigation the behavior of estimators when data is changes a little
3. Week  A robustness discussion about linear regression coefficient and correlation coefficient
4. Week  Modelling of location parameter and related ideas
5. Week  M-estimators for location parameters and distribution properties
6. Week  L-estimators, weighting function
7. Week  Dispersion estimators
8. Week  M-estimatorss for scale parameters
9. Week  Applications for M-estimators: robust confidence interval and hypothesis testing
10. Week  Measuring robustness
11. Week  Mid-term exam
12. Week  Influence function of estimators and applications, Breakdown point of estimators and applications
13. Week  Maximum asymptotic bias
14. Week  Estimates of functional
15. Week  Influence function of M-estimators
16. Week  Final exam
 -- RECOMMENDED OR REQUIRED READING
  Huber, P. J., 1981. "Robust statistics" Wiley, Newyork Maronna, R. A., Martin, R. D., Yohai, V. J., 2006. "Robust statistics: Theory and Methods
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Lecture
 -- WORK PLACEMENT(S)
  ----
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
1
40
 Assignment
0
0
 Exercises
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Contribution of In-term Studies to Overall Grade  
40
 Contribution of Final Examination to Overall Grade  
60
 -- WORKLOAD
 Efficiency  Total Week Count  Weekly Duration (in hour)  Total Workload in Semester
 Theoretical Study Hours of Course Per Week
14
3
42
 Practising Hours of Course Per Week
0
0
0
 Reading
10
3
30
 Searching in Internet and Library
10
4
40
 Designing and Applying Materials
0
0
0
 Preparing Reports
10
3
30
 Preparing Presentation
5
3
15
 Presentation
5
3
15
 Mid-Term and Studying for Mid-Term
3
3
9
 Final and Studying for Final
3
3
9
 Other
0
0
0
 TOTAL WORKLOAD: 
190
 TOTAL WORKLOAD / 25: 
7.6
 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