STAT 504 | Course Introduction and Application Information - Applied Mathematics and Statistics – With Thesis

Course Name

Nonparametric Statistics

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
STAT 504	Fall/Spring	3	0	3	7.5

Prerequisites	None
Course Language	English
Course Type	Elective
Course Level	Second Cycle
Mode of Delivery	-
Teaching Methods and Techniques of the Course	Problem Solving Q&A
National Occupation Classification	-
Course Coordinator	-
Course Lecturer(s)	Prof. Dr. İsmihan BAYRAMOĞLU
Assistant(s)	Arş.Gör. Merve KAHRAMAN ARİMAN

Course Objectives	The objective of this course is to understand the nonparametric approach and to use some of the basic nonparametric techniques.
Learning Outcomes	The students who succeeded in this course; will be able to use key concepts of nonparametric statistics to explore random samples. will be able to apply the approximate nonparamteric statistical techniques. will be able to use order statistics. will be able to apply of randomness based on runs. will be able to solve general two-sample problems. will be able to discuss linear rank statistics.
Course Description	Most of the nonparametric techniques are based on order statistics, runs, and ranks. Therefore the theory of order statistics, runs, and rank statistics is extensively studied.
Related Sustainable Development Goals

Course Category	Core Courses
	Major Area Courses
	Supportive Courses
	Media and Management Skills Courses
	Transferable Skill Courses

Week	Subjects	Related Preparation
1	Order statistics, quantiles, and coverages	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618
2	Distributional properties of order statistics	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618
3	Empirical distribution function	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618
4	Tests of randomness (run statistics)	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker.
5	Distribution theory of runs	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618
6	Goodness of fit tests	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618
7	The Chis-quare goodness of fit test	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618
8	Kolmogorov Smirnov tests	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618
9	The general two sample problem	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618
10	The general two sample problem	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618
11	Linear rank statistics	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker.
12	Measures of association	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618
13	Measures of association	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618
14	Applications	“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618
15	Semester review
16	Final exam

Course Notes/Textbooks

“Nonparametric Statistical Inference” by J. D. Gibbons and S. Chakraborti, Marcel Dekker, Marcel Dekker Inc,3rd Revised edition,1992. ISBN-13: 978-0824786618

Suggested Readings/Materials

“Introduction to the Theory of Nonparametric Statistics” by R.H. Randles and D. A. Wolfe, John Wiley & Sons,1979. ISBN-13: 0471042455 9780471042457

Semester Activities	Number	Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury	1	10
Project	1	20
Seminar / Workshop
Oral Exams
Midterm	1	30
Final Exam	1	40
Total

Weighting of Semester Activities on the Final Grade	3	60
Weighting of End-of-Semester Activities on the Final Grade	1	40
Total

Semester Activities	Number	Duration (Hours)	Workload
Theoretical Course Hours (Including exam week: 16 x total hours)	16	3	48
Laboratory / Application Hours (Including exam week: '.16.' x total hours)	16		0
Study Hours Out of Class	14	5	70
Field Work			0
Quizzes / Studio Critiques			0
Portfolio			0
Homework / Assignments			0
Presentation / Jury	1	22	22
Project	1	30	30
Seminar / Workshop			0
Oral Exam			0
Midterms	1	25	25
Final Exam	1	30	30
		Total	225

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Program Competencies/Outcomes

* Contribution Level

1

2

3

4

5

1

To be able to demonstrate independent and critical thinking in Applied Mathematics and Statistics.

-

X

2

To be able to define problems in Applied Mathematics/Statistics and verify whether they are mathematically/statistically consistent.

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X

-

3

To be able to analyse and solve real life problems using applied methods and interdisciplinary approach of Mathematics/Statistics.

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4

To be able to independently conduct, conclude, and report on specialized research in Applied Mathematics and Statistics.

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X

-

5

To be able to efficiently use national and international resources, for staying updated in the field, communicating with colleagues, and following the related literature.

-

X

-

6

To be able to develop proficiency in using computer software widely utilized in the fields of Applied Mathematics and Statistics.

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X

-

7

To be able to evaluate solution processes efficiently using mathematical reasoning and modeling in order to contribute to the solutions of social and scientific problems.

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8

To be able to synthesize theoretical frameworks with practical applications through mathematical and statistical methods.

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9

To be able to develop strategies, policies and plans for problems and research areas in Applied Mathematics/Statistics in order to interpret the results and translate them into practice.

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10

To be able to translate key topics, events, and phenomena in Applied Mathematics and Statistics into the context of other scientific disciplines.

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11

To be able to engage in lifelong learning by continuously updating and improving knowledge and skills in Applied Mathematics and Statistics.

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STAT 504 | Course Introduction and Application Information

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