| Academic Year |
2024Year |
School/Graduate School |
Graduate School of Advanced Science and Engineering (Master's Course) |
| Lecture Code |
WRA11401 |
Subject Classification |
Specialized Education |
| Subject Name |
データビジュアライゼーションＢ |
Subject Name
（Katakana） |
データビジュアライゼーションビー |
Subject Name in
English |
Data Visualization B |
| Instructor |
To be announced. |
Instructor
(Katakana) |
タントウキョウインミテイ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
1st-Year, Second Semester, Intensive |
| Days, Periods, and Classrooms |
(Int) Inte |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
|
| Lecture・ Work |
| Credits |
1.0 |
Class Hours/Week |
|
Language of Instruction |
E
:
English |
| Course Level |
5
:
Graduate Basic
|
| Course Area（Area） |
24
:
Social Sciences |
| Course Area（Discipline） |
03
:
Economics |
| Eligible Students |
|
| Keywords |
Quantitative data, descriptive statistics, visualization |
| 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) | |
|---|
Class Objectives
/Class Outline |
This course is about the data visualization with PC excise. The data visualization became more important in recent year because of improving access for big data. In the data Visualization B, we study how to visualize results of statistical estimation. The source provides lecture of basic concepts and PC implementation. The goal is to obtain the skill of data-visualization and data-driven conversation. |
| Class Schedule |
lesson1 Introduction
lesson2 Estimation of population characteristics (Concept 1)
lesson3 Estimation of population characteristics (Concept 2)
lesson4 Visualization for estimation result, PC excise, and mid-term report
lesson5 Statistical prediction (Concept 1)
lesson6 Statistical prediction (Concept 2)
lesson7 Visualization for prediction results, PC excise, and mid-term report
lesson8 Final report
lesson9
lesson10
lesson11
lesson12
lesson13
lesson14
lesson15
Report
<Class Schedule>
|
Text/Reference
Books,etc. |
Data Visualization: A Practical Introduction (Kieran Healy) |
PC or AV used in
Class,etc. |
|
| (More Details) |
Text・Handout・Picture（Video/PC/Other） |
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
If it is first time to use R, you should carefully review class contents |
| Requirements |
|
| Grading Method |
Report, Quiz, Oral presentation, Attitude toward the class
Final report (60%)
Mid-term report (30%)
Participation for class-room discussion (10%)
|
| 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. |