Hiroshima University Syllabus

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Japanese
Academic Year 2024Year School/Graduate School School of Science
Lecture Code HB395040 Subject Classification Specialized Education
Subject Name 数学情報課題研究
Subject Name
(Katakana)
スウガクジョウホウカダイケンキュウ
Subject Name in
English
Special Study of Mathematics and Informatics for Graduation
Instructor ODA RYOYA
Instructor
(Katakana)
オダ リョウヤ
Campus Higashi-Hiroshima Semester/Term 4th-Year,  Second Semester,  Second Semester
Days, Periods, and Classrooms (2nd) Inte
Lesson Style Research Lesson Style
(More Details)
 
seminar and discussion 
Credits 5.0 Class Hours/Week   Language of Instruction J : Japanese
Course Level 4 : Undergraduate Advanced
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 01 : Mathematics/Statistics
Eligible Students undergraduate students
Keywords Statistics 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students)
 
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students)
Mathematics
(Abilities and Skills)
・To acquire basic mathematical abilities (Ability to understand concepts, calculation ability, argumentation ability).
・To acquire skills to formulate and solve mathematical questions.
・To learn basic knowledge, skills, and attitudes related to information. Based on them, to be able to process, output and input information, as well as to utilize information appropriately.
(Comprehensive Abilities)
・Acquiring a ability to think logically.
・To acquire ability to utilize mathematical thinking.
・To acquire the ability to understand sentences and communicate information.
・To improve one's ability to learn independently.
・Acquiring a mannar of tackling problems 
Class Objectives
/Class Outline
We shall aquire the knowledge of statistical methods and theory about it. 
Class Schedule lesson1
seminar
lesson2
seminar
lesson3
seminar
lesson4
seminar
lesson5
seminar
lesson6
seminar
lesson7
seminar
lesson8
seminar
lesson9
seminar
lesson10
seminar
lesson11
seminar
lesson12
seminar
lesson13
seminar
lesson14
seminar
lesson15
seminar 
Text/Reference
Books,etc.
「R・Pythonによる統計データ科学」杉山 高一・藤越康祝,勉誠出版
「情報量規準」小西 貞則・北川 源四郎, 朝倉書店 
PC or AV used in
Class,etc.
 
(More Details) personal computor 
Learning techniques to be incorporated  
Suggestions on
Preparation and
Review
every lesson: preparation of seminar 
Requirements  
Grading Method We judge  by the quality of preparation of every lesson. 
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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