| Academic Year |
2024Year |
School/Graduate School |
Graduate School of Humanities and Social Sciences (Master's Course) Division of Educational Sciences International Education Development Program |
| Lecture Code |
WNE01901 |
Subject Classification |
Specialized Education |
| Subject Name |
Introduction of Statistical Analysis in Education |
Subject Name
（Katakana） |
キョウイクトウケイガイロン |
Subject Name in
English |
Introduction of Statistical Analysis in Education |
| Instructor |
SHIMIZU KINYA |
Instructor
(Katakana) |
シミズ キンヤ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
1st-Year, Second Semester, 4Term |
| Days, Periods, and Classrooms |
(4T) Fri1-4：IDEC 207 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
|
| Lecture and actual application of statistical theories using a calculator. |
| Credits |
2.0 |
Class Hours/Week |
|
Language of Instruction |
E
:
English |
| Course Level |
5
:
Graduate Basic
|
| Course Area（Area） |
24
:
Social Sciences |
| Course Area（Discipline） |
07
:
Education |
| Eligible Students |
Mainly for IDEC students in Educational development |
| Keywords |
Statistical analysis, educational research |
| 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 will introduce the basic concepts and methods of statistical analysis (in Education.) The course will provide lectures and exercises on descriptive variables, statistical inference, analysis of bivariate relationships, categorical data analysis, and bivariate regression and correlation.
Although the instructor will provide a series of lectures on this subject, students are responsible to present their own solution for each exercise in class.
|
| Class Schedule |
week 1 Introduction
week 2 Chapter 1: Statistics in the Research Process and Problems
week 3 Chapter 1: Statistics in the Research Process and Problems
week 4 Chapter 2: Describing Variables & Problems
week 5 Chapter 2: Describing Variables & Problems
week 6 Chapter 2: Describing Variables & Problems
week 7 Review and Problems
week 8 MID-TERM EXAM
week 9 Chapter 3: Inferences about Means
week 10 Chapter 3: Inferences about Means
week 11 Chapter 4: Analysis of Variance
week 12 Chapter 4: Analysis of Categoric Data
week 13 Chapter 5: Analysis of Categoric Data
week 14 Review and Problems
week 15 FINAL EXAM
|
Text/Reference
Books,etc. |
Statistics for the behavioral sciences｜Maruzen eBook Library(https://elib.maruzen.co.jp/elib/html/BookDetail/Id/3000046676?0) |
PC or AV used in
Class,etc. |
|
| (More Details) |
Students must be able to use Calculator |
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
(1) Students must read each chapter in advance, (2)students must solve all problems on the text prior to the second class on that chapter |
| Requirements |
This class will be taught in English only. Thus, it requires an advanced level of English proficiency. |
| Grading Method |
Grading:
Proportion of evaluation
1 Attendance 10%
2 Assignments and Presentation of solutions 30%
3 Mid-Term Exam 30%
4 Final Exam 30%
[Allocation of points in grades]
Scores Grade in IDEC
100-90% A
89-80% A
79-70% B
69-60% C
BELOW 59%（Fail） D
|
| 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. |