Hiroshima University Syllabus

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Academic Year 2022Year School/Graduate School School of Informatics and Data Science
Lecture Code KA217001 Subject Classification Specialized Education
Subject Name ノンパラメトリック解析
Subject Name
Subject Name in
Nonparametric analysis
ワカキ ヒロフミ
Campus Higashi-Hiroshima Semester/Term 3rd-Year,  First Semester,  2Term
Days, Periods, and Classrooms (2T) Weds7-8, (2T) Fri5-6:ENG 103
Lesson Style Lecture Lesson Style
(More Details)
Lecture and exercise.
Credits 2.0 Class Hours/Week   Language of Instruction B : Japanese/English
Course Level 3 : Undergraduate High-Intermediate
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 01 : Mathematics/Statistics
Eligible Students
Keywords Wilcoxon's signed rank test, Mann-Whitney U test, Ansari-Bradley test, Kolmogorov-Smirnov test, Kruskal-Wallis test. 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
A subject to be leaned after studying basic statistical inferences 
Criterion referenced
Informatics and Data Science Program
(Knowledge and Understanding)
・D1. Knowledge and skills required for understanding the theoretical system of statistics and data analysis, and for precisely and efficiently analyzing qualitative/quantitative information in big data.

(Abilities and Skills)
・A. Skills related to the development of an information infrastructure,information processing techniques, and technology for producing new added value through data analysis.
Class Objectives
/Class Outline
Learn about the theory of nonparametric tests, and exercises with using R. 
Class Schedule lesson1:Influence on the t-test by non normality (lecture)
lesson2:Using R (Exercize)
lesson3:Influence on the t-test by non normality (exercise)
lesson4:Wilkoxon's signed rank test (lecture)
lesson5:Wilkoxon's signed rank test (exercise)
lesson6:Wilkoxon's rank sum test - Mann-Whitney U test (lecture)
lesson7:Wilkoxon's rank sum test - Mann-Whitney U test (exercise)
lesson8:Influence on the Bartlett's test by non normality (lecture)
lesson9:Influence on the Bartlett's test by non normality (exercise)
lesson10:Ansari-Bradley test (lecture)
lesson11:Ansari-Bradley test (exercise)
lesson12:Kolmogorov-Smirnov test (lecture)
lesson13:Kolmogorov-Smirnov test (exercise)
lesson14:ANOVA and Kruskal-Walis test (lecture)
sson15:ANOVA and Kruskal-Walis test (exercise)

PC or AV used in
(More Details) PC (Laptop as a Requisite Tool) 
Learning techniques to be incorporated  
Suggestions on
Preparation and
Ask questions soon in the class or after the class if you cannot understand 
Grading Method reports 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. 
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