| 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. |