CC221503 Descriptive Statistics

Hiroshima University Syllabus

Japanese

Academic Year 2026Year School/Graduate School School of Education

Lecture Code CC221503 Subject Classification Specialized Education

Subject Name 数理統計学概論

Subject Name
（Katakana）スウリトウケイガクガイロン

Subject Name in
English Descriptive Statistics

Instructor MONDEN REI

Instructor
(Katakana) モンデン　レイ

Campus Higashi-Hiroshima Semester/Term 2nd-Year, First Semester, 1Term

Days, Periods, and Classrooms (1T) Tues5-8：EDU K201

Lesson Style Lecture Lesson Style
(More Details) Face-to-face

Lecture-oriented, Note-taking

Credits 2.0 Class Hours/Week 4 Language of Instruction J : Japanese

Course Level 2 : Undergraduate Low-Intermediate

Course Area（Area） 25 : Science and Technology

Course Area（Discipline） 01 : Mathematics/Statistics

Eligible Students

Keywords The basics of mathematical 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) Program in Mathematics Education
（Knowledge and Understanding）
・To understand basic knowledge of teaching contents of mathematic education.
（Abilities and Skills）
・To acquire and utilize the ability to think mathematically about teaching contents of mathematic education such as algebra, geometry, statistics and computer.

Computer Science Program
（Abilities and Skills）
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.
・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis.

Data Science Program
（Knowledge and Understanding）
・D1. Knowledge and ability to understand the theoretical framework of statistics and data analysis and to analyze qualitative/quantitative information of big data accurately and efficiently.
（Abilities and Skills）
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.
・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis.

Intelligence Science Program
（Knowledge and Understanding）
・D1. A deep systematic understanding of the advanced intelligence of human beings and its realization by computers.
（Abilities and Skills）
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.
・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis.

Class Objectives
/Class Outline The objectives of this course are:
- to enhance education and teaching skills of statistics,
- to acquire the basic knowledge of mathematical statistics
- to acquire mathematical thinking and unique ways of thinking concerning statistics, and
- learn to apply statistics to real data

Class Schedule Lesson1: Guidance, What is Statistics? Extraction of Data and Samples

Lesson2: Frequency Distribution

Lesson3: Center Characteristic Value

Lesson4: Variation in Characteristic Value

Lesson5:Corelation

Lesson6: Regression

Lesson7: Probability, Discrete Probability Distribution

Lesson8; Continuous Probability Distribution

Lesson9: Sample Distribution1

Lesson10: Sample Distribution2

Lesson11:Point Estimation

Lesson12: Interval Estimation1

Lesson13: Interval Estimation2

Lesson14: Hypothesis Testing

Lesson15: Exam

The course will be assessed by one report and a final examination.

Text/Reference
Books,etc. The course will be conducted using handouts rather than a prescribed textbook. However, the following references are recommended as useful supplementary resources for a deeper understanding of the course content:
Illowsky & Dean, Introductory Statistics 2e (OpenStax)

PC or AV used in
Class,etc. Handouts, Microsoft Teams, moodle

(More Details) Textbook, Handouts, PC

Learning techniques to be incorporated Quizzes/ Quiz format, Post-class Report

Suggestions on
Preparation and
Review In mathematic statistics, you need to understand the logic of statistics about data, rather than just solving formulas in order. You sometime cannot understand solved formulas if you do not have knowledge of statistics. You should try to understand the logic of statistics through this course and prepare for and review each lesson well. This lecture will be provided by face-to-face format, only.

As out-of-class study, for preparation, students should read the relevant sections of the handouts in advance and review the basic terminology, definitions, and theorems. For review, students are expected to work through the formulas and examples covered in class on their own and be able to explain their meaning. In addition, students should study not only the calculation procedures themselves, but also the statistical way of thinking on which those procedures are based.

Requirements None.

Grading Method a report(40%), an exam(55%), attitude toward class participation(5%)

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.

Academic Year	2026Year	School/Graduate School	School of Education
Lecture Code	CC221503	Subject Classification	Specialized Education
Subject Name	数理統計学概論
Subject Name （Katakana）	スウリトウケイガクガイロン
Subject Name in English	Descriptive Statistics
Instructor	MONDEN REI
Instructor (Katakana)	モンデン　レイ
Campus	Higashi-Hiroshima	Semester/Term	2nd-Year, First Semester, 1Term
Days, Periods, and Classrooms	(1T) Tues5-8：EDU K201
Lesson Style	Lecture	Lesson Style (More Details)	Face-to-face
Lecture-oriented, Note-taking
Credits	2.0	Class Hours/Week	4	Language of Instruction	J : Japanese
Course Level	2 : Undergraduate Low-Intermediate
Course Area（Area）	25 : Science and Technology
Course Area（Discipline）	01 : Mathematics/Statistics
Eligible Students
Keywords	The basics of mathematical 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)	Program in Mathematics Education （Knowledge and Understanding）・To understand basic knowledge of teaching contents of mathematic education. （Abilities and Skills）・To acquire and utilize the ability to think mathematically about teaching contents of mathematic education such as algebra, geometry, statistics and computer. Computer Science Program （Abilities and Skills）・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value. ・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis. Data Science Program （Knowledge and Understanding）・D1. Knowledge and ability to understand the theoretical framework of statistics and data analysis and to analyze qualitative/quantitative information of big data accurately and efficiently. （Abilities and Skills）・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value. ・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis. Intelligence Science Program （Knowledge and Understanding）・D1. A deep systematic understanding of the advanced intelligence of human beings and its realization by computers. （Abilities and Skills）・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value. ・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis.
Class Objectives /Class Outline	The objectives of this course are: - to enhance education and teaching skills of statistics, - to acquire the basic knowledge of mathematical statistics - to acquire mathematical thinking and unique ways of thinking concerning statistics, and - learn to apply statistics to real data
Class Schedule	Lesson1: Guidance, What is Statistics? Extraction of Data and Samples Lesson2: Frequency Distribution Lesson3: Center Characteristic Value Lesson4: Variation in Characteristic Value Lesson5:Corelation Lesson6: Regression Lesson7: Probability, Discrete Probability Distribution Lesson8; Continuous Probability Distribution Lesson9: Sample Distribution1 Lesson10: Sample Distribution2 Lesson11:Point Estimation Lesson12: Interval Estimation1 Lesson13: Interval Estimation2 Lesson14: Hypothesis Testing Lesson15: Exam The course will be assessed by one report and a final examination.
Text/Reference Books,etc.	The course will be conducted using handouts rather than a prescribed textbook. However, the following references are recommended as useful supplementary resources for a deeper understanding of the course content: Illowsky & Dean, Introductory Statistics 2e (OpenStax)
PC or AV used in Class,etc.	Handouts, Microsoft Teams, moodle
(More Details)	Textbook, Handouts, PC
Learning techniques to be incorporated	Quizzes/ Quiz format, Post-class Report
Suggestions on Preparation and Review	In mathematic statistics, you need to understand the logic of statistics about data, rather than just solving formulas in order. You sometime cannot understand solved formulas if you do not have knowledge of statistics. You should try to understand the logic of statistics through this course and prepare for and review each lesson well. This lecture will be provided by face-to-face format, only. As out-of-class study, for preparation, students should read the relevant sections of the handouts in advance and review the basic terminology, definitions, and theorems. For review, students are expected to work through the formulas and examples covered in class on their own and be able to explain their meaning. In addition, students should study not only the calculation procedures themselves, but also the statistical way of thinking on which those procedures are based.
Requirements	None.
Grading Method	a report(40%), an exam(55%), attitude toward class participation(5%)
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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