| Academic Year |
2025Year |
School/Graduate School |
Graduate School of Humanities and Social Sciences (Master's Course) Division of Educational Sciences Education Data Science Program |
| Lecture Code |
WNF02000 |
Subject Classification |
Specialized Education |
| Subject Name |
統計解析の基礎 |
Subject Name
（Katakana） |
|
Subject Name in
English |
Basics of Statistical Analysis |
| Instructor |
TOYA AKIHIRO,HASHIMOTO JUNYA |
Instructor
(Katakana) |
トヤ アキヒロ,ハシモト ジュンヤ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
1st-Year, First Semester, 1Term |
| Days, Periods, and Classrooms |
(1T) Fri1-4：EDU K216 |
| Lesson Style |
Seminar |
Lesson Style
(More Details) |
Face-to-face, Online (on-demand) |
| Practice-Centered |
| Credits |
2.0 |
Class Hours/Week |
4 |
Language of Instruction |
J
:
Japanese |
| Course Level |
5
:
Graduate Basic
|
| Course Area（Area） |
24
:
Social Sciences |
| Course Area（Discipline） |
05
:
Sociology |
| Eligible Students |
|
| Keywords |
Statistical Analysis, R |
| 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 |
Students will learn how to analyze social phenomena using statistics. This guide explains how to perform basic statistical analysis using the statistical analysis software, R. |
| Class Schedule |
lesson1 Orientation: Explanation of the course overview
lesson2 Installation of R and RStudio, and basic usage (Lecture & Practice)
lesson3 Data handling with R: Lecture
lesson4 Data handling with R: Practice
lesson5 Data visualization with R: Lecture
lesson6 Data visualization with R: Practice
lesson7 Descriptive and inferential statistics with R: Lecture
lesson8 Descriptive and inferential statistics with R: Practice
lesson9 Statistical hypothesis testing: Lecture
lesson10 Statistical hypothesis testing: Practice
lesson11 Relationship between two variables: Lecture
lesson12 Relationship between two variables: Practice
lesson13 Advanced Statistical Analysis: Lecture
lesson14 Advanced Statistical Analysis: Practice
lesson15 Summary
A small assignment will be given in each class. |
Text/Reference
Books,etc. |
【Textbook】シュミュラー, J. 笠田 実 (訳) (2023). Rで基礎から学ぶ統計学 東京化学同人 |
PC or AV used in
Class,etc. |
Text, Handouts, Visual Materials, Microsoft Teams, moodle |
| (More Details) |
|
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
Please thoroughly read the content of the corresponding text for each session and make sure to prepare and review in advance. If you encounter any difficulties executing R, consult the responsible instructor as needed. |
| Requirements |
'Basics of Statistical Analysis' is a common subject for both Social Data Science Program and Education Data Science Program. This course (Lecture Code: WNF02000) is for the Education Data Science Program. Students in the Social Data Science Program should take 'Basics of Statistical Analysis' (Lecture Code: WMK00300) designed for Social Data Science Program. |
| Grading Method |
Evaluation will be based on the small assignments given in each class, as well as the final report assignment. |
| 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. |