Hiroshima University Syllabus

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Japanese
Academic Year 2022Year School/Graduate School Common Graduate Courses (Doctoral Course)
Lecture Code 8E550101 Subject Classification Common Graduate Courses
Subject Name データサイエンス
Subject Name
(Katakana)
データサイエンス
Subject Name in
English
Data Science
Instructor YANAGIHARA HIROKAZU,SOLVANG HIROKO
Instructor
(Katakana)
ヤナギハラ ヒロカズ,ソルヴァン ヒロコ
Campus Higashi-Hiroshima Semester/Term 1st-Year,  Second Semester,  3Term
Days, Periods, and Classrooms (3T) Mon7-8,Weds9-10:IMC-Main 2F PC Rm
Lesson Style Lecture Lesson Style
(More Details)
 
Lecture using power point and blackboard, practical training of data analysis 
Credits 2.0 Class Hours/Week   Language of Instruction J : Japanese
Course Level 5 : Graduate Basic
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 01 : Mathematics/Statistics
Eligible Students
Keywords Data reading & processing, Data visualization, Data analysis 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Program
This course is one of the elective subjects, in "Career Development and Data Literacy Courses", Common Graduate Courses that aims to learn about the development of the current social systems, to gain knowledge needed for the future, to specifically tackle the challenges facing modern society and to acquire the ability to use knowledge and skills. 
Criterion referenced
Evaluation
 
Class Objectives
/Class Outline
We study data reading, data processing, data analysis, and perform the exercise using the R.  
Class Schedule lesson1 Explanation of the lecture(YANAGIHARA)
lesson2 Basic operation of the R(YANAGIHARA)
lesson3 Data reading(YANAGIHARA)
lesson4 Studying the shape of data distribution(YANAGIHARA)
lesson5 Data filing and searching(YANAGIHARA)
lesson6 Scatter plot and correlation coefficient(YANAGIHARA)
lesson7 Single regression analysis(YANAGIHARA)
lesson8 Hypothesis testing for difference between means(YANAGIHARA)
lesson9 Data Analysis in Practice 1(SOLVANG)
lesson10 Data Analysis in Practice 2(SOLVANG)
lesson11 Data Analysis in Practice 3(SOLVANG)
lesson12 Data Analysis in Practice 4(SOLVANG)
lesson13 Data Analysis in Practice 5(SOLVANG)
lesson14 Data Analysis in Practice 6(SOLVANG)
lesson15 Data Analysis in Practice 7(SOLVANG) 
Text/Reference
Books,etc.
Not specified 
PC or AV used in
Class,etc.
 
(More Details) Blackboard, power-point, PC 
Learning techniques to be incorporated  
Suggestions on
Preparation and
Review
Please do not hesitate to ask a question if you have dubious points. 
Requirements  
Grading Method Report 
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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