ISB302 NonParametric Statistics

5 ECTS - 3-0 Duration (T+A)- 6. Semester- 3 National Credit

Information

Unit FACULTY OF SCIENCE AND LETTERS
STATISTICS PR.
Code ISB302
Name NonParametric Statistics
Term 2019-2020 Academic Year
Semester 6. Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 5 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Lisans Dersi
Type Normal
Label C Compulsory
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. SADULLAH SAKALLIOĞLU
Course Instructor Prof. Dr. SADULLAH SAKALLIOĞLU (Bahar) (A Group) (Ins. in Charge)


Course Goal / Objective

Selecting the appropriate tests to test hypotheses and gain the ability to apply non-parametric tests

Course Content

Basic concepts, the difference between parametric and nonparametric statistics, one sample tests, related two sample tests, independent two samples tests.

Course Precondition

Resources

Notes

W. J. Conover (1998). Practical Nonparametric Statistics, Wiley; 3rd edition.


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Distinguish the difference between parametric and nonparametric statistical methods,
LO02 Understand which method you can use
LO03 Apply sign test and Wilcoxon signed rank test
LO04 Apply median test and Mann-Whitney U test
LO05 Apply Mood test and Moses test
LO06 Use related two sample tests
LO07 Use k independent sample test and approximation to chi-square statistics
LO08 Use Friedman S test and approximation to chi-square test
LO09 Perform goodness of fit tests


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 - Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics 2
PLO02 - Emphasize the importance of Statistics in life 1
PLO03 - Define basic principles and concepts in the field of Law and Economics 0
PLO04 - Produce numeric and statistical solutions in order to overcome the problems 3
PLO05 - Use proper methods and techniques to gather and/or to arrange the data 2
PLO06 - Utilize computer systems and softwares 4
PLO07 - Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events 5
PLO08 - Apply the statistical analyze methods 0
PLO09 - Make statistical inference(estimation, hypothesis tests etc.) 0
PLO10 - Generate solutions for the problems in other disciplines by using statistical techniques 1
PLO11 - Discover the visual, database and web programming techniques and posses the ability of writing programme 3
PLO12 - Construct a model and analyze it by using statistical packages 0
PLO13 - Distinguish the difference between the statistical methods 0
PLO14 - Be aware of the interaction between the disciplines related to statistics 0
PLO15 - Make oral and visual presentation for the results of statistical methods 0
PLO16 - Have capability on effective and productive work in a group and individually 4
PLO17 - Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs 3
PLO18 - Develop scientific and ethical values in the fields of statistics-and scientific data collection 3


Week Plan

Week Topic Preparation Methods
1 Basic concepts Source reading
2 the difference between parametric and nonparametric technics Source reading
3 Levels of Measurement Source reading
4 one sample tests: sign test, Wilcoxon signed rank test Source reading
5 independent two samples tests: median test, Mann-Whitney test Source reading
6 independent two samples tests: Mood test, Moses Source reading
7 related two sample tests: sign test, Wilcoxon signed rank test Source reading
8 Mid-Term Exam Written exam
9 chi square test of independence Source reading
10 independent k samples test:Kruskal-Wallis Test (H statistics) Source reading
11 sampling distribution of H statistics and chi-square approximation Source reading
12 Friedman S Test Source reading
13 sampling distribution of S statistics and chi-square approximation Source reading
14 Goodness of fit tests Source reading
15 Solving problem Review of topics discussed in the lecture notes and sources
16 Term Exams Written exam
17 Term Exams Written exam


Assessment (Exam) Methods and Criteria

Assessment Type Midterm / Year Impact End of Term / End of Year Impact
1. Midterm Exam 100 20
General Assessment
Midterm / Year Total 100 20
1. Final Exam - 80
Grand Total - 100


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 3 42
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 12 12
Final Exam 1 18 18
Total Workload (Hour) 114
Total Workload / 25 (h) 4,56
ECTS 5 ECTS

Update Time: 29.04.2025 02:18