| Academic Year |
2024Year |
School/Graduate School |
School of Informatics and Data Science |
| Lecture Code |
KA114001 |
Subject Classification |
Specialized Education |
| Subject Name |
統計的検定 |
Subject Name
（Katakana） |
トウケイテキケンテイ |
Subject Name in
English |
Statistical Test |
| Instructor |
YAMAMURA MARIKO,YANAGIHARA HIROKAZU |
Instructor
(Katakana) |
ヤマムラ マリコ,ヤナギハラ ヒロカズ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
2nd-Year, First Semester, 2Term |
| Days, Periods, and Classrooms |
(2T) Fri1-4：ECON B257 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
|
| Lecture, Quiz |
| Credits |
2.0 |
Class Hours/Week |
|
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 |
|
| 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) | 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 |
Understand and use the statistical hypothesis test |
| Class Schedule |
lesson1 Introduction
lesson2 Descriptive and inferential statistics
lesson3 Statistical distribution
lesson4 Exercise: Statistical distribution
lesson5 Law of large numbers and central limited theorem
lesson6 Confidential interval
lesson7 Exercise: Confidential interval
lesson8 Hypothesis test for mean
lesson9 Exercise: Hypothesis test for mean
lesson10 Hypothesis test for ratio
lesson11 Exercise: Hypothesis test for ratio
lesson12 Power and sample size
lesson13 Exercise: Power and sample size
lesson14 Multiple comparison
lesson15 Test |
Text/Reference
Books,etc. |
None |
PC or AV used in
Class,etc. |
|
| (More Details) |
Text |
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
Understand every classes |
| Requirements |
|
| Grading Method |
Contribution to the class, Test, Answer to problems |
| 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. |