GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
NONPARAMETRİC STATİSTİCS/5291303
Course Title: NONPARAMETRİC STATİSTİCS
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 concepts of the order statistics and rank-order statistics
To learn the concepts of distributions of order statistics
To learn the concepts of test statistics based on runs and their distributions
To learn the concepts of test statistics and their distributions for one sample
To learn the concepts of test statistics and their distributions for two independent samples
To learn the concepts of test statistics and their distributions for k independent samples
To learn the concepts of test statistics and their distributions for two-way classification
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face.
 --WEEKLY SCHEDULE
1. Week  order statistics , rank-order statistics
2. Week  the distributions of order statistics , test statistics for run
3. Week  the sign test and calculation of power
4. Week  Wilcoxon signed rank test statistic and its distribution
5. Week  the median test statistic and its distribution for two independent samples
6. Week  Wald-Wolfowitz test statistic and its distribution
7. Week   Mann-Whitney test statistic and its distribution
8. Week   Mood test statistic and Siegel-Tukey test statistic and their distributions
9. Week  Midterm exams
10. Week  Freund-Ansari-Bradley and David- Barton test statistics and their distributions
11. Week  Kruskal-Wallis H test statistic and its distribution
12. Week  the test statistics for ordered alternatives
13. Week  the test statistics for ordered alternatives
14. Week  the test statistics for umbrella alternatives
15. Week  Mack-Skilling T test
16. Week  Final exams
 -- 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  
50
 Percentage of Final Exam to Total Score  
50
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
10
2
20
 Searching in Internet and Library
10
2
20
 Material Design and Implementation
0
 Report Preparing
2
17
34
 Preparing a Presentation
0
 Presentation
0
 Midterm Exam and Preperation for Midterm Exam
2
18
36
 Final Exam and Preperation for Final Exam
2
18
36
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
188
 TOTAL WORKLOAD / 25: 
7.52
 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. Hamza GAMGAM)
 -- WEB SITE(S) OF LECTURER(S)
   (http://websitem.gazi.edu.tr/site/gamgam)
 -- EMAIL(S) OF LECTURER(S)
   (gamgam@gazi.edu.tr)