Hiroshima University Syllabus

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Japanese
Academic Year 2022Year School/Graduate School School of Informatics and Data Science
Lecture Code KA114001 Subject Classification Specialized Education
Subject Name 統計的検定
Subject Name
(Katakana)
トウケイテキケンテイ
Subject Name in
English
Statistical Test
Instructor IMORI SHINPEI
Instructor
(Katakana)
イモリ シンペイ
Campus Higashi-Hiroshima Semester/Term 2nd-Year,  First Semester,  2Term
Days, Periods, and Classrooms (2T) Fri1-4:ENG 220
Lesson Style Lecture Lesson Style
(More Details)
 
 
Credits 2.0 Class Hours/Week   Language of Instruction B : Japanese/English
Course Level 2 : Undergraduate Low-Intermediate
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 01 : Mathematics/Statistics
Eligible Students
Keywords Hypothesis test, SDG_04 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Program
 
Criterion referenced
Evaluation
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.

・ B. Ability to identify and solve new problems on their own by quantitative and logical thinking based on data, diverse perspectives, and advanced skills for information processing and analysis.
 
Class Objectives
/Class Outline
Understand the statistical hypothesis test 
Class Schedule lesson1  Introduction
lesson2  Statistical inference
lesson3  What is hypothesis testing?
lesson4  Two-sample problem
lesson5  Test for population mean
lesson6  Test for population ratio
lesson7  Test for population variance
lesson8 Test for normality
lesson9  Likelihood ratio test
lesson10 Chi-square test for goodness of fit and test for independency
lesson11  Analysis of variance
lesson12  Usage of statistical software R
lesson13  Exercise
lesson14  Exercise
lesson15  Conclusion

Quiz and report

The class schedule may be changed.  
Text/Reference
Books,etc.
None 
PC or AV used in
Class,etc.
 
(More Details) PC 
Learning techniques to be incorporated  
Suggestions on
Preparation and
Review
Check the handout before and after each class 
Requirements  
Grading Method Attitude (20%), Quiz (40%) and report (40%) 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
Message  
Other   
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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